Showing papers by "Cranfield University published in 2016"

Design for additive manufacturing: trends, opportunities, considerations, and constraints

Abstract: The past few decades have seen substantial growth in Additive Manufacturing (AM) technologies. However, this growth has mainly been process-driven. The evolution of engineering design to take advantage of the possibilities afforded by AM and to manage the constraints associated with the technology has lagged behind. This paper presents the major opportunities, constraints, and economic considerations for Design for Additive Manufacturing. It explores issues related to design and redesign for direct and indirect AM production. It also highlights key industrial applications, outlines future challenges, and identifies promising directions for research and the exploitation of AM's full potential in industry.

Wire + Arc Additive Manufacturing

Abstract: Depositing large components (>10 kg) in titanium, aluminium, steel and other metals is possible using Wire + Arc Additive Manufacturing. This technology adopts arc welding tools and wire as feedstock for additive manufacturing purposes. High deposition rates, low material and equipment costs, and good structural integrity make Wire+Arc Additive Manufacturing a suitable candidate for replacing the current method of manufacturing from solid billets or large forgings, especially with regards to low and medium complexity parts. A variety of components have been successfully manufactured with this process, including Ti–6Al–4V spars and landing gear assemblies, aluminium wing ribs, steel wind tunnel models and cones. Strategies on how to manage residual stress, improve mechanical properties and eliminate defects such as porosity are suggested. Finally, the benefits of non-destructive testing, online monitoring and in situ machining are discussed.

Sustainability‐oriented Innovation: A Systematic Review

Abstract: This article is intended as a contribution to the ongoing conceptual development of Sustainability-Oriented Innovation (SOI) and provides initial guidance on becoming and being sustainable. We organize and integrate the diverse body of empirical literature relating to SOI and, in doing so, develop a synthesized conceptual framework onto which SOI practices and processes can be mapped. SOI involves making intentional changes to an organization’s philosophy and values, as well as to its products, processes or practices to serve the specific purpose of creating and realising social and environmental value in addition to economic returns. A critical reading of previous literature relating to environmental management and sustainability reveals how little attention has been paid to SOI and what exists is only partial. In a review of 100 scholarly articles and 27 grey sources drawn from the period of the three Earth Summits (1992, 2002 and 2012), we address four specific deficiencies that have given rise to these limitations: the meaning of SOI, how it has been conceptualised, its treatment as a dichotomous phenomenon and a general failure to reflect more contemporary practices. We adopt a framework synthesis approach involving first constructing an initial architecture of the landscape grounded in previous studies which is subsequently iteratively tested, shaped, refined and reinforced into a model of SOI with data drawn from included studies: so advancing theoretical development in the field of SOI.

An overview of advances in biomass gasification

Abstract: Biomass gasification is a widely used thermochemical process for obtaining products with more value and potential applications than the raw material itself. Cutting-edge, innovative and economical gasification techniques with high efficiencies are a prerequisite for the development of this technology. This paper delivers an assessment on the fundamentals such as feedstock types, the impact of different operating parameters, tar formation and cracking, and modelling approaches for biomass gasification. Furthermore, the authors comparatively discuss various conventional mechanisms for gasification as well as recent advances in biomass gasification. Unique gasifiers along with multi-generation strategies are discussed as a means to promote this technology into alternative applications, which require higher flexibility and greater efficiency. A strategy to improve the feasibility and sustainability of biomass gasification is via technological advancement and the minimization of socio-environmental effects. This paper sheds light on diverse areas of biomass gasification as a potentially sustainable and environmentally friendly technology.

A review on electric vehicle battery modelling: From Lithium-ion toward Lithium–Sulphur

Abstract: Accurate prediction of range of an electric vehicle (EV) is a significant issue and a key market qualifier. EV range forecasting can be made practicable through the application of advanced modelling and estimation techniques. Battery modelling and state-of-charge estimation methods play a vital role in this area. In addition, battery modelling is essential for safe charging/discharging and optimal usage of batteries. Much existing work has been carried out on incumbent Lithium-ion (Li-ion) technologies, but these are reaching their theoretical limits and modern research is also exploring promising next-generation technologies such as Lithium–Sulphur (Li–S). This study reviews and discusses various battery modelling approaches including mathematical models, electrochemical models and electrical equivalent circuit models. After a general survey, the study explores the specific application of battery models in EV battery management systems, where models may have low fidelity to be fast enough to run in real-time applications. Two main categories are considered: reduced-order electrochemical models and equivalent circuit models. The particular challenges associated with Li–S batteries are explored, and it is concluded that the state-of-the-art in battery modelling is not sufficient for this chemistry, and new modelling approaches are needed.

Stability and Scalability of Homogeneous Vehicular Platoon: Study on the Influence of Information Flow Topologies

Abstract: In addition to decentralized controllers, the information flow among vehicles can significantly affect the dynamics of a platoon. This paper studies the influence of information flow topology on the internal stability and scalability of homogeneous vehicular platoons moving in a rigid formation. A linearized vehicle longitudinal dynamic model is derived using the exact feedback linearization technique, which accommodates the inertial delay of powertrain dynamics. Directed graphs are adopted to describe different types of allowable information flow interconnecting vehicles, including both radar-based sensors and vehicle-to-vehicle (V2V) communications. Under linear feedback controllers, a unified internal stability theorem is proved by using the algebraic graph theory and Routh–Hurwitz stability criterion. The theorem explicitly establishes the stabilizing thresholds of linear controller gains for platoons, under a large class of different information flow topologies. Using matrix eigenvalue analysis, the scalability is investigated for platoons under two typical information flow topologies, i.e., 1) the stability margin of platoon decays to zero as $0(\mbox{1}/N^{2})$ for bidirectional topology; and 2) the stability margin is always bounded and independent of the platoon size for bidirectional-leader topology. Numerical simulations are used to illustrate the results.

Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling

Abstract: Battery health monitoring and management is of extreme importance for the performance and cost of electric vehicles. This paper is concerned with machine-learning-enabled battery state-of-health (SOH) indication and prognosis. The sample entropy of short voltage sequence is used as an effective signature of capacity loss. Advanced sparse Bayesian predictive modeling (SBPM) methodology is employed to capture the underlying correspondence between the capacity loss and sample entropy. The SBPM-based SOH monitor is compared with a polynomial model developed in our prior work. The proposed approach allows for an analytical integration of temperature effects such that an explicitly temperature-perspective SOH estimator is established, whose performance and complexity is contrasted to the support vector machine (SVM) scheme. The forecast of remaining useful life is also performed via a combination of SBPM and bootstrap sampling concepts. Large amounts of experimental data from multiple lithium-ion battery cells at three different temperatures are deployed for model construction, verification, and comparison. Such a multi-cell setting is more useful and valuable than only considering a single cell (a common scenario). This is the first known application of combined sample entropy and SBPM to battery health prognosis.

A Conceptual Framework for Circular Design

Abstract: Design has been recognised in the literature as a catalyst to move away from the traditional model of take-make-dispose to achieve a more restorative, regenerative and circular economy. As such, for a circular economy to thrive, products need to be designed for closed loops, as well as be adapted to generate revenues. This should not only be at the point of purchase, but also during use, and be supported by low-cost return chains and reprocessing structures, as well as effective policy and regulation. To date, most academic and grey literature on the circular economy has focused primarily on the development of new business models, with some of the latter studies addressing design strategies for a circular economy, specifically in the area of resource cycles and design for product life extension. However, these studies primarily consider a limited spectrum of the technical and biological cycles where materials are recovered and restored and nutrients (e.g., materials, energy, water) are regenerated. This provides little guidance or clarity for designers wishing to design for new circular business models in practice. As such, this paper aims to address this gap by systematically analysing previous literature on Design for Sustainability (DfX) (e.g., design for resource conservation, design for slowing resource loops and whole systems design) and links these approaches to the current literature on circular business models. A conceptual framework is developed for circular economy design strategies. From this conceptual framework, recommendations are made to enable designers to fully consider the holistic implications for design within a circular economy.

How Business Customers Judge Solutions: Solution Quality and Value in Use

Abstract: Many manufacturers look to business solutions to provide growth; however, success is far from guaranteed, and it is unclear how such solutions can create superior perceived value. This article explores what constitutes value for customers from solutions over time—conceptualized as “value in use”—and how this arises from quality perceptions of the solution’s components. The authors develop a framework for solution quality and value in use through 36 interviews combining repertory grid technique and means-end chains. The findings significantly extend the extant view of quality as a function of the supplier’s products and services, and show that customers also assess the quality of their own resources and processes, as well as the quality of the joint resource integration process. The authors report that value in use corresponds not just to collective, organizational goals but also to individuals’ goals, a finding that strongly contrasts with prior research. Four moderators of the quality–value relat...

Real-Time Trajectory Planning for Autonomous Urban Driving: Framework, Algorithms, and Verifications

Abstract: This paper focuses on the real-time trajectory planning problem for autonomous vehicles driving in realistic urban environments. To solve the complex navigation problem, we adopt a hierarchical motion planning framework. First, a rough reference path is extracted from the digital map using commands from the high-level behavioral planner. The conjugate gradient nonlinear optimization algorithm and the cubic B-spline curve are employed to smoothen and interpolate the reference path sequentially. To follow the refined reference path as well as handle both static and moving objects, the trajectory planning task is decoupled into lateral and longitudinal planning problems within the curvilinear coordinate framework. A rich set of kinematically feasible path candidates are generated to deal with the dynamic traffic both deliberatively and reactively. In the meanwhile, the velocity profile generation is performed to improve driving safety and comfort. After that, the generated trajectories are carefully evaluated by an objective function, which combines behavioral decisions by reasoning about the traffic situations. The optimal collision-free, smooth, and dynamically feasible trajectory is selected and transformed into commands executed by the low-level lateral and longitudinal controllers. Field experiments have been carried out with our test autonomous vehicle on the realistic inner-city roads. The experimental results demonstrated capabilities and effectiveness of the proposed trajectory planning framework and algorithms to safely handle a variety of typical driving scenarios, such as static and moving objects avoidance, lane keeping, and vehicle following, while respecting the traffic rules.

The strengthening effect of inter-layer cold working and post-deposition heat treatment on the additively manufactured Al–6.3Cu alloy

Abstract: Wire + Arc Additive Manufacture (WAAM) attracts great interest from the aerospace industry for producing components with aluminum alloys, particularly Al–Cu alloy of the 2000 series such as 2219 alloy. However the application is restricted by the low strength properties of the as-deposited WAAM metal. In this study two strengthening methods were investigated – inter-layer cold working and post-deposition heat treatment. Straight wall samples were prepared with 2319 aluminum alloy wire. Inter-layer rolling with loads of 15 kN, 30 kN and 45 kN were employed during deposition. The ultimate tensile strength (UTS) and yield strength (YS) of the inter-layer rolled alloy with 45 kN load can achieve 314 MPa and 244 MPa respectively. The influence of post-deposition T6 heat treatment was investigated on the WAAM alloy with or without rolling. Compared with inter-layer rolling, post-deposition heat treatment can provide much greater enhancement of the strength. After T6 treatment, the UTS and YS of both of the as-deposited and 45 kN rolled alloys exceeded 450 MPa and 305 MPa respectively, which are higher than the properties of the wrought 2219−T6 alloy. The strengthening mechanisms of this additively manufactured Al–6.3Cu alloy were investigated through microstructure analysis.

Biomass resources and biofuels potential for the production of transportation fuels in Nigeria

Abstract: Solid biomass and waste are major sources of energy. They account for about 80% of total primary energy consumed in Nigeria. This paper assesses the biomass resources (agricultural, forest, urban, and other wastes) available in Nigeria and the potential for biofuel production from first, second, third and fourth generation biomass feedstocks. It reviews the scope of biomass conversion technologies tested within the country and the reports on the technology readiness level of each. Currently, most of the emerging biofuels projects in Nigeria utilize first generation biomass feedstock for biofuel production and are typically located many miles away from the petroleum refineries infrastructures. These feedstocks are predominantly food crops and thus in competition with food production. With significant availability of non-food biomass resources, particularly in the Niger Delta region of Nigeria, and the petroleum refineries located in the same area, it is pertinent to consider expanding use of the petroleum refinery׳s infrastructure to co-process non-food biomass into bio-intermediate oil for blending with petroleum. This not only addresses the potential food versus fuel conflict challenging biofuel production in Nigeria, but also reduces the cost of setting up new bio-refineries thus eliminating the transportation of ethanol to existing petroleum refineries for blending. In view of this, it is recommended that further research be carried out to assess the feasibility of upgrading existing refineries in Nigeria to co-process bio-based fuels and petroleum products thus achieving the targets set by the Nigeria Energy Commission for biofuel production in the country.

Continuous maintenance and the future – Foundations and technological challenges

Abstract: High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security.

Distributed manufacturing: scope, challenges and opportunities

Abstract: This discussion paper aims to set out the key challenges and opportunities emerging from distributed manufacturing (DM). We begin by describing the concept, available definitions and consider its evolution where recent production technology developments (such as additive and continuous production process technologies), digitisation together with infrastructural developments (in terms of IoT and big data) provide new opportunities. To further explore the evolving nature of DM, the authors, each of whom are involved in specific applications of DM research, examine through an expert panel workshop environment emerging DM applications involving new production and supporting infrastructural technologies. This paper presents these generalisable findings on DM challenges and opportunities in terms of products, enabling production technologies and the impact on the wider production and industrial system. Industry structure and location of activities are examined in terms of the democratising impact on participating network actors. The paper concludes with a discussion on the changing nature of manufacturing as a result of DM, from the traditional centralised, large-scale, long lead-time forecast-driven production operations to a new DM paradigm where manufacturing is a decentralised, autonomous near end user-driven activity. A forward research agenda is proposed that considers the impact of DM on the industrial and urban landscape.

A Comparative Study of Multiple-Criteria Decision-Making Methods under Stochastic Inputs

Abstract: This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative.

Analysis of human mobility patterns from GPS trajectories and contextual information

Abstract: Human mobility is important for understanding the evolution of size and structure of urban areas, the spatial distribution of facilities, and the provision of transportation services. Until recently, exploring human mobility in detail was challenging because data collection methods consisted of cumbersome manual travel surveys, space-time diaries, or interviews. The development of location-aware sensors has significantly altered the possibilities for acquiring detailed data on human movements. Although this has spurred many methodological developments in identifying human movement patterns, many of these methods operate solely from the analytical perspective and ignore the environmental context within which the movement takes place. In this paper we attempt to widen this view and present an integrated approach to the analysis of human mobility using a combination of volunteered GPS trajectories and contextual spatial information. We propose a new framework for the identification of dynamic travel modes and static significant places behaviour using trajectory segmentation, data mining, and spatio-temporal analysis. We are interested in examining if and how travel modes depend on the residential location, age, or gender of the tracked individuals. Further, we explore theorised ‘third places’, which are spaces beyond main locations home/work where individuals spend time to socialise. Can these places be identified from GPS traces? We evaluate our framework using a collection of trajectories from 205 volunteers linked to contextual spatial information on the types of places visited and the transport routes they use. The result of this study is a contextually enriched data set that supports new possibilities for modelling human movement behaviour.

Estimating the soil clay content and organic matter by means of different calibration methods of vis-NIR diffuse reflectance spectroscopy

Abstract: The selection of calibration method is one of the main factors influencing measurement accuracy of soil properties estimation in visible and near infrared reflectance spectroscopy. In this study, the performance of three regression techniques, namely, partial least-squares regression (PLSR), support vector regression (SVR), and multivariate adaptive regression splines (MARS) were compared to identify the best method to assess organic matter (OM) and clay content in the salt-affected soils. One hundred and two soil samples collected from Northern Sinai, Egypt, were used as the data set for the calibration and validation procedures. The dry samples were scanned using a FieldSpec Pro FR Portable Spectroradiometer (Analytical Spectral Devices, ASD) with a measurement range of 350–2500 nm. The spectra were subjected to seven pre-processed techniques, e.g., Savitzky–Golay (SG) smoothing, first derivative with SG smoothing (FD-SG), second derivative with SG smoothing (SD-SG), continuum removed reflectance (CR), standard normal variate and detrending (SNV-DT), multiplicative scatter correction (MSC) and extended MSC. The results of cross-validation showed that in most cases MARS models performed better than PLSR and SVR models. The best predictions were obtained using MARS calibration methods with CR prep-processing, yielding R2, root mean squared error (RMSE), and ratio of performance to deviation (RPD) values of 0.85, 0.19%, and 2.63, respectively, for OM; and 0.90, 5.32%, and 3.15, respectively, for clay content.