Imperial College London


Faculty of EngineeringDyson School of Design Engineering

Chair and Leader in Engineering Design



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Publication Type

222 results found

Yu Z, SMHadi S, Hasitha W, Childs P, Nanayakkara Tet al., 2021, A method to use reservoir computing in a whisker sensor for terrain identification by mobile robots, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems

This paper shows analytical and experimental evidence of using the vibration dynamics of a compliant whisker for accurate terrain classification during steady state motion of a mobile robot. A Hall effect sensor was used to measure whisker vibrations due to perturbations from the ground. Analytical results predict that the whisker vibrations will have a dominant frequency at the vertical perturbation frequency of the mobile robot sandwiched by two other less dominant but distinct frequency components. These frequency components may come from bifurcation of vibration frequency due to nonlinear interaction dynamics at steady state. Experimental results also exhibit distinct dominant frequency components unique to the speed of the robot and the terrain roughness. This nonlinear dynamic feature is used in a deep multi-layer perceptron neural network to classify terrains. We achieved 85.6% prediction success rate for seven flat terrain surfaces with different textures.Index Terms— Robotic whiskers, Surface identification, multi-layer perceptron, Modal analysis.

Conference paper

Han J, Jiang P, Childs PRN, 2021, Metrics for Measuring Sustainable Product Design Concepts, ENERGIES, Vol: 14

Journal article

Park D, Han J, Childs PRN, 2021, 266 Fuzzy front-end studies: current state and future directions for new product development, Research in Engineering Design, Vol: 32, Pages: 377-409, ISSN: 0934-9839

266 fuzzy front-end (FFE) studies in the new product development (NPD) sector were examined. The studies were selected using a bibliometrics method, and chronologically and statistically examined with ten criteria divided into two dimensions. The first dimension is associated with overall attributes of the FFE, consisting of six criteria: the study taxonomy, model type, NPD speed, NPD attributes, model characteristic, and model structure. The second dimension is relevant to the FFE performance structure related to process parameters, comprised of four criteria: the FFE task, activity, performance method, and toolkit. In terms of those two dimensions, the paper looks at previous FFE studies to gain an understanding of features of each FFE study along with related knowledge and theories, as well as identification of evolution trends of FFE studies. Based on the identification, an FFE model development strategy for each criterion is formulated, and this paper proposes possible options for executing those strategies which exert influence on the form of the cluster network. The intention is for the database to be utilised as an overview of all existing FFE studies and allow specific FFE studies to be selected to examine FFE approaches.This paper provides FFE model development guidance on how to deal with the overall attributes and outcomes of the FFE which affect the entirety of the innovation process, and how to manage the performance structure related to process parameters.

Journal article

Park D, Han J, Childs PRN, 2021, A data-driven fuzzy front end model for contextual performance and concurrent collaboration, IEEE Transactions on Engineering Management, Pages: 1-24, ISSN: 0018-9391

A data-driven model for the fuzzy front end (FFE) stage in new product development (NPD) programs, with a series of toolkits to decrease uncertainty and ambiguity of parameter processing, has been developed. Parameters produced in toolkits provided in previous models tend to exist independently, without any interrelationship in the contextual performance relationship of a single functional domain nor concurrent collaboration relationship across multiple functional domains. This results in uncertainty and ambiguity triggered by an incorrect interpretation of parameters. The new model involved inferring a single representative FFE scenario wherein diverse FFE performance structures interlock from the contextual performance and concurrent collaboration perspectives by analyzing various real-world FFE scenarios gathered from NPD expert interviews. This representative scenario was embodied into the model with a performative structure, through deployment of toolkits. Users are informed of the purpose, roles, and meanings of parameters and their relationships and thus can infer each parameter from other parameters. This contributes to reduction in uncertainty and ambiguity in processing parameters. This article proposes an FFE execution concept, giving mathematical reasoning behind the performance structure of the model.

Journal article

Wang P, Wang S, Peng D, Chen L, Wu C, Wei Z, Childs P, Guo Y, Li Let al., 2020, Neurocognition-inspired design with machine learning, Design Science, Vol: 6, Pages: 1-19, ISSN: 2053-4701

Generating designs via machine learning has been an on-going challenge in computer-aided design. Recently, deep learning methods have been applied to randomly generate images in fashion, furniture and product design. However, such deep generative methods usually require a large number of training images and human aspects are not taken into account in the design process. In this work, we seek a way to involve human cognitive factors through brain activity indicated by electroencephalographic measurements (EEG) in the generative process. We propose a neuroscience-inspired design with a machine learning method where EEG is used to capture preferred design features. Such signals are used as a condition in generative adversarial networks (GAN). First, we employ a recurrent neural network Long Short-Term Memory as an encoder to extract EEG features from raw EEG signals; this data are recorded from subjects viewing several categories of images from ImageNet. Second, we train a GAN model conditioned on the encoded EEG features to generate design images. Third, we use the model to generate design images from a subject’s EEG measured brain activity. To verify our proposed generative design method, we present a case study, in which the subjects imagine the products they prefer, and the corresponding EEG signals are recorded and reconstructed by our model for evaluation. The results indicate that a generated product image with preference EEG signals gains more preference than those generated without EEG signals. Overall, we propose a neuroscience-inspired artificial intelligence design method for generating a design taking into account human preference. The method could help improve communication between designers and clients where clients might not be able to express design requests clearly.

Journal article

Simpson K, Whyte J, Childs P, 2020, Data-centric innovation in retrofit: A bibliometric review of dwelling retrofit across North Western Europe, Energy and Buildings, Vol: 229, Pages: 1-9, ISSN: 0378-7788

Data-centric innovation can inform the development of effective retrofit strategies through novel methods of collecting, analysing and sharing data. This bibliometric review uses a text-mining tool to identify research trends in dwelling retrofit research across North Western Europe. The review identifies a major focus on energy efficiency, with sub-themes on: 1) energy performance, 2) heat, power and control technologies, 3) indoor environment quality and 4) retrofit practice. In dwelling retrofit, there is now an established research tradition of using data-centric methods in monitoring and modelling energy performance to inform and learn from energy efficiency interventions. Building on the state-of-the-art, our analyses suggest opportunities for data-centric methods to consider the indoor environment quality and material impacts resulting from energy performance improvements. This information can then be openly communicated across the supply chain. Thus the paper discusses the retrofit themes and data-centric methods within North Western Europe, for an emerging trajectory of data-centric retrofit research and practice.

Journal article

Baxter W, Roots S, Tuomala E, Aurisicchio M, Rodrigues PS, Ratcliffe E, Childs P, Martin N, Saclier Cet al., 2020, Ritual Design Toolkit, London, Publisher: Interaction Foundry

Rituals are intentional behaviours with a distinct emotional outcome. They fill our lives with deeper meaning and are found everywhere from the workplace to the kitchen table. We have made the Ritual Design Toolkit to help you understand rituals, how to harness them, and how to design them. In our own work, we have used the toolkit in a range of applications including enhancing key moments in a customer journey, helping people adopt healthier eating habits and building and strengthening communities. The toolkit can be used for grand rituals and micro-interactions. Whether you are a manager of a team, a packaging designer, or a service enthusiast, you can find guidance here to build more meaningful moments into your work. The toolkit offers a ritual design process consisting of three main steps: scoping, creating and testing rituals.


Spyrakos-Papastavridis E, Childs PRN, Dai JS, 2020, Passivity Preservation for Variable Impedance Control of Compliant Robots, IEEE-ASME TRANSACTIONS ON MECHATRONICS, Vol: 25, Pages: 2342-2353, ISSN: 1083-4435

Journal article

Liu X, Ouyang M, Orzech M, Niu Y, Tang W, Chen J, Naylor Marlow M, Puhan D, Zhao Y, Tan R, Brankin C, Haworth N, Zhao S, Wang H, Childs P, Margadonna S, Wagemaker M, Pan F, Brandon N, George C, Wu Bet al., 2020, In-situ fabrication of carbon-metal fabrics as freestanding electrodes for high-performance flexible energy storage devices, Energy Storage Materials, Vol: 30, Pages: 329-336, ISSN: 2405-8297

Hierarchical 1D carbon structures are attractive due to their mechanical, chemical and electrochemical properties however the synthesis of these materials can be costly and complicated. Here, through the combination of inexpensive acetylacetonate salts of Ni, Co and Fe with a solution of polyacrylonitrile (PAN), self-assembling carbon-metal fabrics (CMFs) containing unique 1D hierarchical structures can be created via easy and low-cost heat treatment without the need for costly catalyst deposition nor a dangerous hydrocarbon atmosphere. Microscopic and spectroscopic measurements show that the CMFs form through the decomposition and exsolution of metal nanoparticle domains which then catalyze the formation of carbon nanotubes through the decomposition by-products of the PAN. These weakly bound nanoparticles form structures similar to trichomes found in plants, with a combination of base-growth, tip-growth and peapod-like structures, where the metal domain exhibits a core(graphitic)-shell(disorder) carbon coating where the thickness is in-line with the metal-carbon binding energy. These CMFs were used as a cathode in a flexible zinc-air battery which exhibited superior performance to pure electrospun carbon fibers, with their metallic nanoparticle domains acting as bifunctional catalysts. This work therefore unlocks a potentially new category of composite metal-carbon fiber based structures for energy storage applications and beyond.

Journal article

Muranko Z, Aurisicchio M, Baxter W, Childs Pet al., 2020, Behaviour chains in circular consumption systems: the reuse of FMCGs, Proceedings of the IS4CE2020 Conference of the International Society for the Circular Economy

Conference paper

Simpson C, Whyte J, Childs P, 2020, Residential retrofit: A review of themes, data-centric methods and future directions to accelerate net zero, CIBSE Technical Symposium

Conference paper

Chen X, Liu X, Ouyang M, Chen J, Taiwo O, Xia Y, Childs P, Brandon N, Wu Bet al., 2019, Multi-metal 4D printing with a desktop electrochemical 3D printer, Scientific Reports, Vol: 9, ISSN: 2045-2322

4D printing has the potential to create complex 3D geometries which are able to react to environmental stimuli opening new design possibilities. However, the vast majority of 4D printing approaches use polymer based materials, which limits the operational temperature. Here, we present a novel multi-metal electrochemical 3D printer which is able to fabricate bimetallic geometries and through the selective deposition of different metals, temperature responsive behaviour can thus be programmed into the printed structure. The concept is demonstrated through a meniscus confined electrochemical 3D printing approach with a multi-print head design with nickel and copper used as exemplar systems but this is transferable to other deposition solutions. Improvements in deposition speed (34% (Cu)-85% (Ni)) are demonstrated with an electrospun nanofibre nib compared to a sponge based approach as the medium for providing hydrostatic back pressure to balance surface tension in order to form a electrolyte meniscus stable. Scanning electron microscopy, X-ray computed tomography and energy dispersive X-ray spectroscopy shows that bimetallic structures with a tightly bound interface can be created, however convex cross sections are created due to uneven current density. Analysis of the thermo-mechanical properties of the printed strips shows that mechanical deformations can be generated in Cu-Ni strips at temperatures up to 300 °C which is due to the thermal expansion coefficient mismatch generating internal stresses in the printed structures. Electrical conductivity measurements show that the bimetallic structures have a conductivity between those of nanocrystalline copper (5.41×106 S.m−1) and nickel (8.2×105 S.m-1). The potential of this novel low-cost multi-metal 3D printing approach is demonstrated with the thermal actuation of an electrical circuit and a range of self-assembling structures.

Journal article

Childs PRN, 2019, Aircraft cabin air supply and the internal air system, Journal of Health and Pollution, Vol: 9, Pages: S17-S21, ISSN: 2156-9614

This paper describes systems commonly employed to deliver aircraftcabin air, and the internal air system which is responsible for thesupply of balancing, sealing and cooling air used with the engine tocontrol the operation of bearings, discs and other critical components,as well as bleed air. A series of mechanisms that could be responsiblefor contamination of bleed and cabin air are considered including:ingestion into the compressor intake of poor quality air; leakage froma seal of oil; ingestion from the gases associated with a stall or surgeevent; off-gassing of cabin fittings and emissions from occupants.

Journal article

Chen X, Liu X, Ouyang M, Childs P, Brandon N, Wu Bet al., 2019, Electrospun composite nanofibre supercapacitors enhanced with electrochemically 3D printed current collectors, Journal of Energy Storage, Vol: 26, Pages: 100993-100993, ISSN: 2352-152X

Carbonised electrospun nanofibres are attractive for supercapacitors due to their relatively high surface area, facile production routes and flexibility. With the addition of materials such as manganese oxide (MnO), the specific capacitance of the carbon nanofibres can be further improved through fast surface redox reactions, however this can reduce the electrical conductivity. In this work, electrochemical 3D printing is used as a novel means of improving electrical conductivity and the current collector-electrode interfacial resistance through the deposition of highly controlled layers of copper. Neat carbonised electrospun electrodes made with a 30 wt% manganese acetylacetonate (MnACAC) and polyacrylonitrile precursor solution have a hydrophobic nature preventing an even copper deposition. However, with an ethanol treatment, the nanofibre films can be made hydrophilic which enhances the copper deposition morphology to enable the formation of a percolating conductive network through the electrode. This has the impact of increasing electrode electronic conductivity by 360% from 10 S/m to 46 S/m and increasing specific capacitance 110% from 99 F/g to 208 F/g at 5 mV/s through increased utilisation of the pseudocapacitive active material. This novel approach thus provides a new route for performance enhancement of electrochemical devices using 3D printing, which opens new design possibilities.

Journal article

Childs P, 2019, Interplays of humanism, cognitivism and behaviourism in design engineering, Design School: After Boundaries and disciplines, Editors: Rodgers, Bremner, Publisher: Vernon Press, ISBN: 978-1-62273-586-0

Principal learning theories include behaviourism, humanism, cognitivism and constructivism. Each has held sway in education for a period and has contributed to our ability to develop and deploy evidence-based curriculums and learning environments. This chapter considers the contributions of these learning theories and their relevance to the design, engineering and hybrid domains, with a particular focus on the recently developed curriculum for an integrated masters in Design Engineering at Imperial College London.

Book chapter

Wang P, Peng D, Li L, Chen L, Wu C, Wang X, Childs P, Guo Yet al., 2019, Human-in-the-loop design with machine learning, The International Conference in Engineering Design (ICED) 19, Publisher: Cambridge University Press (CUP), Pages: 2577-2586

Deep learning methods have been applied to randomly generate images, such as in fashion, furniture design. To date, consideration of human aspects which play a vital role in a design process has not been given significant attention in deep learning approaches. In this paper, results are reported from a human- in-the-loop design method where brain EEG signals are used to capture preferable design features. In the framework developed, an encoder extracting EEG features from raw signals recorded from subjects when viewing images from ImageNet are learned. Secondly, a GAN model is trained conditioned on the encoded EEG features to generate design images. Thirdly, the trained model is used to generate design images from a person's EEG measured brain activity in the cognitive process of thinking about a design. To verify the proposed method, a case study is presented following the proposed approach. The results indicate that the method can generate preferred designs styles guided by the preference related brain signals. In addition, this method could also help improve communication between designers and clients where clients might not be able to express design requests clearly.

Conference paper

Hu Z, Rao C, Tao C, Childs PRN, Zhao Yet al., 2019, A case-based decision theory based process model to aid product conceptual design, Cluster Computing, Vol: 22, Pages: 10145-10162, ISSN: 1386-7857

In new product development, the rapid proposal of innovative solutions represents an important phase. This in turn relies on creative ideas, their evaluation, refinement and embodiment of worthwhile directions. This study aims to describe a CBDT based process model for product conceptual design that concentrates on rapidly generating innovations with the support of decision-making rationale. Case-based decision theory (CBDT), derived from case-based reasoning, is applied in this paper as a core method to aid design engineers to make an informed decision quickly, thus accelerating the design process. In the process of utilizing CBDT to support a decision, as for the similarity function, the proper value assignment methods to the selected attribute set for calculation are discussed. In order to assist with innovative solution, aspects of the theory of inventive problem solving (TRIZ) are integrated into the case-based reasoning process. Accordingly, a CBDT-TRIZ model is developed. Quality-function deployment is used to translate customer wants into relevant engineering design requirements and thus formulating the design specification. Image-Scale is used to offer an orthogonal coordinates system to aid evaluation. Finally, a case study is used to demonstrate the validity of the proposed process model based on the design of a cordless hand-tool for garden and lawn applications.

Journal article

Chen L, Wang P, Dong H, Shi F, Han J, Guo Y, Childs PRN, Xiao J, Wu Cet al., 2019, An artificial intelligence based data-driven approach for design ideation, Journal of Visual Communication and Image Representation, Vol: 61, Pages: 10-22, ISSN: 1047-3203

Ideation is a source of innovation and creativity, and is commonly used in early stages of engineering design processes. This paper proposes an integrated approach for enhancing design ideation by applying artificial intelligence and data mining techniques. This approach consists of two models, a semantic ideation network and a visual concepts combination model, which provide inspiration semantically and visually based on computational creativity theory. The semantic ideation network aims to provoke new ideas by mining potential knowledge connections across multiple knowledge domains, and this was achieved by applying “step-forward” and “path-track” algorithms which assist in exploring forward given a concept and in tracking back the paths going from a departure concept through a destination concept. In the visual concepts combination model, a generative adversarial networks model is proposed for generating images which synthesize two distinct concepts. An implementation of these two models was developed and tested in a design case study, which indicated that the proposed approach is able to not only generate a variety of cross-domain concept associations but also advance the ideation process quickly and easily in terms of quantity and novelty.

Journal article

Garvey B, Chen L, Shi F, Han J, Childs Pet al., 2019, New directions in computational, combinational and structural creativity, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Vol: 233, Pages: 425-431, ISSN: 0954-4062

This paper examines how new and creative relationships in data sets, not easily revealed by conventional information retrieval methods and technologies, can be identified using a mix of established and new methods. The authors present how the integration of computerised Morphological Analysis with new computational models, incorporating web crawler, data processing networking and data mining algorithms, can help facilitate the identification of new ideas. Boden’s concept of “Combinational Creativity” indicates a structured process which generates unfamiliar combinations of familiar concepts and constructs allowing creative styles of thought. This structured approach has been constrained by the resultant combinatorial explosion and the dearth of easily accessible computer software and supporting methodologies, to help identify viable new solutions. Feature enhanced computerised morphological analysis (MA), provides a new structural support tool for creativity and innovation. MA systematically structures and examines all the possible relationships in a multidimensional, highly complex, usually non-quantifiable problem space. Computerisation of the process now permits large numbers of configurations (millions) in the problem space to be majorly reduced (typically > 95%), identifying only internally consistent solutions. These solutions are likely to embrace configurations containing something which has not previously been considered, thus increasing the probability of some form of technological or design breakthrough and hence truly creative.

Journal article

Han J, Park D, Shi F, Chen L, Hua M, Childs PRNet al., 2019, Three driven approaches to combinational creativity: Problem-, similarity- and inspiration-driven, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Vol: 233, Pages: 373-384, ISSN: 0954-4062

Creativity is a crucial element of design. The aim of this study is to investigate the driving forces behind combinational creativity. We propose three driven approaches to combinational creativity, problem-, similarity- and inspiration-driven, based on previous research projects on design process, strategy and cognition. A case study involving hundreds of practical products selected from winners of international design competitions has been conducted to evaluate the three approaches proposed. The results support the three driven approaches and indicate that they can be used independently as well as complementarily. The three approaches proposed in this study have provided an understanding of how combinational creativity functions in design. The approaches could be used as a set of creative idea generation methods for supporting designers in producing creative design ideas.

Journal article

Childs P, Cropley D, 2019, Creativity in design special section, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Vol: 233, Pages: 371-372, ISSN: 0954-4062

Journal article

Childs PRN, 2018, Mechanical Design Engineering Handbook, Publisher: Butterworth-Heinemann, ISBN: 9780081023679

Presents a clear, concise text that explains key component technology, with step-by-step procedures, fully worked design scenarios, component images and cross-sectional line drawings Provides essential data, equations and interactive ...


Han J, Shi F, Chen L, Childs PRNet al., 2018, A computational tool for creative idea generation based on analogical reasoning and ontology, AI EDAM, Vol: 32, Pages: 462-477, ISSN: 0890-0604

Analogy is a core cognition process used to produce inferences as well as new ideas using previous knowledge and experience. Ontology is a formal representation of a set of domain concepts and their relationships. The use of analogy and ontology in design activities to support design creativity have previously been explored. This paper explores an approach to construct ontologies with sufficient richness and coverage to support reasoning over real-world datasets for prompting creative idea generation. This approach has been implemented into a computational tool for assisting designers in generating creative ideas during the early stages of design. The tool, called “the Retriever”, has been developed based on ontology by embracing the aspects of analogical reasoning. A case study has indicated that the tool can be effective and useful for idea generation. The results have indicated that the tool, in its current formulation, can significantly improve the fluency and flexibility of idea generation and the usefulness of ideas, as well as slightly increase the originality of ideas, for the case study concerned.

Journal article

Michalakoudis I, Aurisicchio M, Childs P, Koutlidis A, Harding Jet al., 2018, Empowering manufacturing personnel through functional understanding, Production Planning and Control, Vol: 29, Pages: 688-703, ISSN: 0953-7287

A growing interest in organizational knowledge management, along with increasingly widespread adoption of Quality Standards such as ISO 9001, has increasingly led organizations to implement training programs for all employees. Training for the manufacturing workforce, however, remains limited to informal “On-the-Job” training, administered by peer colleagues or supervisors - particularly in Small and Medium Enterprises (SMEs) where economic, educational, cognitive and cultural constraints to training are often deeply embedded. This paper proposes a methodology for training the manufacturing workforce on the functions of products and their constituent parts, and presents a case study conducted in a UK-based manufacturing SME - aiming to verify our two research hypotheses: Functional Analysis Diagrams (FAD) of the company’s products and parts would assist in knowledge assimilation; and, the knowledge assimilation has a positive effect on work quality and productivity levels. This intervention provided training on the purpose of the processes the participants are involved, aiming to empower them in supporting the optimization of these same processes. By using surveys and applying statistical inference on long-term quantitative data, the study confirmed subjective observations of substantial improvements in work quality (scrap reduction of 63%) and increased productivity (setup time reduced by 67%). To our knowledge, we were the first to examine the effect of functional modelling methods for workforce training in a manufacturing setup. Although this paper presents a single case study, the results suggest that the proposed methodology can be a promising solution for the industry.

Journal article

Han J, Shi F, Chen L, Childs Pet al., 2018, The Combinator – a computer-based tool for creative idea generation based on a simulation approach, Design Science, Vol: 4, ISSN: 2053-4701

Idea generation is significant in design, but coming up with creative ideas is often challenging. This paper presents a computer-based tool, called the Combinator, for assisting designers to produce creative ideas. The tool is developed based on an approach simulating aspects of human cognition in achieving combinational creativity. It can generate combinational prompts in text and image forms through combining unrelated ideas. A case study has been conducted to evaluate the Combinator. The study results indicate that the Combinator, in its current formulation, has assisted the tool users involved in the case study in improving the fluency of idea generation, as well as increasing the originality, usefulness, and flexibility of the ideas generated. The results also indicate that the tool could benefit its users in generating high-novelty and high-quality ideas effectively. The Combinator is considered to be beneficial in expanding the design space, increasing better idea occurrence, improving design space exploration, and enhancing the design success rate.

Journal article

Chen L, Wang P, Shi F, Han J, Childs PRNet al., 2018, A COMPUTATIONAL APPROACH FOR COMBINATIONAL CREATIVITY IN DESIGN, 15th International Design Conference, Publisher: Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Croatia; The Design Society, Glasgow, UK

Conference paper

Spyrakos-Papastavridis E, Kashiri N, Childs PRN, Tsagarakis NGet al., 2018, Online impedance regulation techniques for compliant humanoid balancing, Robotics and Autonomous Systems, Vol: 104, Pages: 85-98, ISSN: 0921-8890

This paper presents three distinct techniques, aimed at the online active impedance regulation of compliant humanoid robots, which endeavours to induce a state of balance to the system once it has been perturbed. The presence of passive elastic elements in the drives powering this class of robots leads to under-actuation, thereby rendering the control of compliant robots an intricate task. Consequently, the impedance regulation procedures proposed in this paper directly account for these elastic elements. In order to acquire an indication of the robot’s state of balance in an online fashion, an energy (Lyapunov) function is introduced, whose sign then allows one to ascertain whether the robot is converging to or diverging from, a desired equilibrium position. Computing this function’s time derivative unequivocally gives the energy-injecting nature of the active stiffness regulation, and reveals that active damping regulation has no bearing on the system’s state of stability. Furthermore, the velocity margin notion is interpreted as a velocity value beyond which the system’s balance might be jeopardized, or below which the robot will be guaranteed to remain stable. As a result, the unidirectional and bidirectional impedance optimization methods rely upon the use of bounds that have been defined based on the energy function’s derivative, in addition to the velocity margin. Contrarily, the third technique’s functionality revolves solely around the use of Lyapunov Stability Margins (LSMs). A series of experiments carried out using the COmpliant huMANoid (COMAN), demonstrates the superior balancing results acquired when using the bidirectional scheme, as compared to utilizing the two alternative techniques.

Journal article

Zhu L, Li N, Childs P, 2018, Light-weighting in aerospace component and system design, Propulsion and Power Research, Vol: 7, Pages: 103-119, ISSN: 2212-540X

Light-weighting involves the use of advanced materials and engineering methods to enable structural elements to deliver the same, or enhanced, technical performance while using less material. The concept has been extensively explored and utilised in many industries from automotive applications to fashion and packaging and offers significant potential in the aviation sector. Typical implementations of light-weighting have involved use of high performance materials such as composites and optimisation of structures using computational aided engineering approaches with production enabled by advanced manufacturing methods such as additive manufacture, foam metals and hot forming. This paper reviews the principal approaches used in light-weighting, along with the scope for application of light-weighting in aviation applications from power-plants to airframe components. A particular area identified as warranting attention and amenable to the use of light-weighting approaches is the design of solar powered aircraft wings. The high aspect ratio typically used for these can be associated with insufficient stiffness, giving rise to non-linear deformation, aileron reversal, flutter and rigid-elastic coupling. Additional applications considered include ultralight aviation components and sub-systems, UAVs, and rockets. Advanced optimisation approaches can be applied to optimise the layout of structural elements, as well as geometrical parameters in order to maximise structural stiffness, minimise mass and enable incorporation of energy storage features. The use of additive manufacturing technologies, some capable of producing composite or multi-material components is an enabler for light-weighting, as features formally associated with one principal function can be designed to fulfil multiple functionalities.

Journal article

Han J, Shi F, Park D, Chen L, Childs PRNet al., 2018, The conceptual distances between ideas in combinational creativity, 15th International Design Conference, Publisher: Design Society, Pages: 1857-1866, ISSN: 1847-9073

Combinational creativity plays a significant role in design for supporting designers in producing creative ideas at early phases of design. This study provides insights into conceptual distances for forming combinational ideas. The results from a case study indicate that far-related ideas are used more often than closely-related ones to produce creative combinational designs and that far-related ideas could lead to more creative outcomes. The study provides new insights to aid designers in understanding the value of combinational creativity, and support in the production of creative designs.

Conference paper

Chen X, Liu X, Childs P, Brandon N, Wu Bet al., 2018, Design and fabrication of a low cost desktop electrochemical 3D printer, Pro-AM Conference in 2014, Pages: 395-400, ISSN: 2424-8967

Copyright © 2018 by Nanyang Technological University. Additive manufacturing (AM) (3D printing) is the process of creating 3D objects from digital models through the layer by layer deposition of materials. Electrochemical additive manufacturing (ECAM) is a relatively new technique which can create metallic components based depositing adherent layers of metal ions onto the surface of conductive substrate. In this paper, the design considerations for a meniscus confined ECAM approach is presented which demonstrates superior print speeds to equivalent works. This is achieved through the increase of the meniscus diameter to 400 \im which was achieved through the integration of a porous sponge into the print head to balance the hydraulic head of the electrolyte. Other piston based methods of controlling the electrolyte meniscus are discussed.

Conference paper

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