To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
We present a mathematical model built to describe the fluid dynamics for the heat transfer fluid in a parabolic trough power plant. Such a power plant consists of a network of tubes for the heat transport fluid. In view of optimisation tasks in the planning and in the operational phase, it is crucial to find a compromise between a very detailed description of many possible physical phenomena and a necessary simplicity needed for a fast and robust computational approach. We present the model, a numerical approach, simulation for single tubes and also for realistic network settings. In addition, we optimise the power output with respect to the operational parameters.
Intravenous fluids are solutions containing various quantities of water, electrolytes, salts, and sugar. They are used to maintain haemostasis when the enteral route is insufficient to meet physiological demand. Fluid therapy maintains hydration, oxygen delivery, and thus organ function. Poor perioperative fluid control is associated with impaired physiological function, resulting in patient harm and increasing healthcare costs. Perioperative fluid management is based upon three distinct but related factors: patient (age and comorbidities), surgical (urgency, indication and duration) and anaesthetic. This chapter is an introduction to intravenous fluids, highlighting the physiological control mechanisms, the composition of intravenous fluids, and important clinical assessment principles.
Companies offer products in different variants to reach more customers. This increases internal variety and cost. However, reducing those cost is difficult due to complexity. Complexity arises from: combinatorics; many design variables interacting with each other; coupling of technical and economical perspectives. This paper presents an approach based on (1) building a complex system model of modular models; (2) identifying the potential for standardization from a technical perspective; (3) cost-optimizing the degree of standardization. A product family of electric vehicles was optimized.
Complexity in systems design can be reduced by computing permissible ranges for some crucial design variables that need to be defined in an early design phase. These ranges are calculated such that there is sufficient tolerance for the remaining design variables in later design phases, while still achieving the overall system design goals. A new algorithm for this approach is presented and applied to the design of a vehicle powertrain mount system. The results show large permissible ranges for mount positions while maintaining sufficient tolerance for mount stiffnesses.
The present analytical design of shrink fits typically results in an uneven stress condition that can lead to failure in a variety of manners. With increasing loads and the use of brittle materials, the optimization of the stresses in the shrink fit hence becomes increasingly necessary. Currently existing approaches do not solve the problem satisfactorily or increase the manufacturing and design effort. This paper therefore considers the implementation of an AI-based stress optimization using reinforcement learning, which performs stress optimization by geometrically contouring the interstice.
Through-Lifecycle Whole Design Design Optimisation is widely considered one of the future approaches to solving design problems featuring prominently in Model-Based Systems Engineering, Set-Based Design and Digital Twins. Yet, design optimisation remains siloed optimising for design subsets. In this paper, we review academic literature and a series of case studies to uncover the challenges in achieving Through-Lifecycle Whole Design Design Optimisation. This is followed by action research that has investigated the application of software deployment toolchains to overcome the challenges.
Compression systems of modern, civil aircraft engines consist of three components: Fan, low-pressure compressor (LPC) and high-pressure compressor (HPC). The efficiency of each component has improved over the last decades by means of rising computational power which made high level aerodynamic optimisations possible. Each component has been addressed individually and separated from the effects of upstream and downstream components. But as much time and effort has been spend to improve performance of rotating components, the stationary inter-compressor duct (ICD) has only received minor attention. With the rotating compression components being highly optimised and sophisticated their performance potential is limited. That is why more aggressive, respectively shorter, ICDs get more and more into the focus of research and engine manufacturers. The length reduction offers high weight saving and thus fuel saving potential as a shorter ICD means a reduction in aircraft engine length. This paper aims at evaluating the impact of more aggressive duct geometries on LPC and HPC performance. A multi objective 3D computational fluid dynamics (CFD) aerodynamic optimisation is performed on a preliminary design of a novel two spool compressor rig incorporating four different operating line and two near-stall (NST) conditions which ensure operability throughout the whole compressor operating range. While the ICD is free to change in length, shape and cross-section area, the blades of LPC and HPC are adjusted for changing duct aerodynamics via profile re-staggering to keep number of free parameters low. With this parametrisation length, reductions for the ICD of up to 40% are feasible while keeping the reduction in isentropic efficiency at aerodynamic design point for the compressor below 1%pt. Three geometries of the Pareto front are analysed in detail focusing on ICD secondary flow behaviour and changes of aerodynamics in LPC and HPC. In order to asses changes in stall margin, speedlines for the three geometries are analysed.
In an effort to add context to a classroom lesson on celestial navigation, we present a numerical adaptation of Captain T.H. Sumner's 1837 journey into St. George's Channel. The adaptation is programmed into a ‘live’ web-based map. This allows for a flexible and highly visual presentation that highlights two important topics in celestial navigation: the origin of the line of position and the scale of maps. Considerations driving the numerical adaptation are discussed, as is as an overview of a classroom lesson we have been using.
The main purpose of this study was to combine the currently separate objectives of aerodynamic performance and manufacturing efficiency, then find an optimal point of operation for both objectives. An additional goal of the study was to explore the effects of changes in design features, the position of the spars, and analyse how the changes influenced the optimal operating conditions. A machine-learning approach was taken to combine and model the gathered aero-manufacturing data, and a multi-objective optimisation approach utilising genetic algorithms was implemented to find the trade-off relationship between optimal target objectives (mission performance and manufacturability). The main achievements and findings of the study were: The study was a success in building a machine-learning model for the combined aero-manufacturing data utilising software library XGBoost; multi-objective optimisation, which did not include spar positions as a variable found the trade-off region between high manufacturability and high mission performance, with choices that offered reasonably high values of both; there was no clearly identified correlation between a small change in spar position and the target objectives; multi-objective optimisation with spar positions resulted in a trade-off relationship between target objectives, which was different from the trade-off relationship found in optimisation without spar positions; multi-objective optimisation with spar positions also offered more flexibility in the choice of manufacturing processes available for a given design; and the range of bump amplitudes for solutions found by multi-objective-optimisation with spar positions was lower and more focused than those found by optimisation without spar positions.
The prescribing of medicines by a range of health professions is pivotal to the success of the future NHS. Prescribing is a key enabler of specialist and advanced practice, and health professionals that can prescribe medicines are crucial members of healthcare delivery teams. Widening the prescribing of medicines to some professions in addition to the medical profession has changed the role boundaries of those prescribing professions, necessitating changes to relationships between those involved in the patient’s care. The teams in which prescribers work are across the full range of professions, extending beyond traditional boundaries, and include consideration of housing, education, employment as well as physical, mental and social health. This diversity has introduced a need for further integrated working and collaboration across the system. Excellent teamwork, clinical governance, communication and information sharing are crucial, as is the need for team members to have a clear understanding of one another’s roles and the ability to communicate with one another.
Industry is a major contributor to climate change. Many industrial sites, supply chains and customers are vulnerable to climate change and policy and consumer responses to climate change. Profits from industrial production depend on consumer demand, and how products are provided. Powerful forces such as digitalisation, dematerialisation, decentralisation, electrification, efficiency improvement and circular economies influence production and emissions Industrial firms face pressure from regulators, investors and customers. However, there is enormous potential to capture multiple benefits through aggressive, innovative decarbonisation strategies that target growth markets and involve cooperation along supply chains. Economic productivity and business competitiveness improvement can cut business costs and reduce extreme weather risk exposure, whilst positioning manufacturing companies for fast-growing markets in low-carbon resilient products and services. The chapter overviews policies national and subnational government policymakers can consider to support transition to a zero-carbon resilient industrial sector.
The objective of this study was to design and evaluate new means of complying to time constraints by presenting aircraft target taxi speeds on a head-up display (HUD). Four different HUD presentations were iteratively developed from paper sketches into digital prototypes. Each HUD presentation reflected different levels of information presentation. A subsequent evaluation included 32 pilots, with varying flight experience, in usability tests. The participants subjectively assessed which information was most useful to comply with time constraints. The assessment was based on six themes including information, workload, situational awareness, stress, support and usability. The evaluation consisted of computer-simulated taxi-runs, self-assessments and statistical analysis. Information provided by a graphical vertical tape descriptive/predictive HUD presentation, including alpha-numerical information redundancy, was rated most useful. Differences between novice and expert pilots can be resolved by incorporating combinations of graphics and alpha-numeric presentations. The findings can be applied for further studies of combining navigational and time-keeping HUD support during taxi.
Multidisciplinary Design Optimization (MDO) is a method that has shown many promising results in the development of complex engineered products. To this date, research on MDO has been extensive, but at the same time, very few publications have addressed the aspect of how it can be taught to students and young professionals. In this light, this paper aims to present the experiences of the authors in respect to the development and management of an MDO course at Linköping University. First, this work will describe the authors' teaching approaches, and in particular, it will present the various educational activities that have been considered over the years as well as the lessons learnt. Secondly, this work will attempt to investigate how students perceive a set of common MDO concepts, and more specifically, it will present an analysis based on the results of two surveys that took place in 2016 and 2020, respectively. Given the above foundation, this paper will try to establish guidelines regarding the activities which are suitable for teaching each concept, while finally, it will also touch upon the challenges as well as the solutions for adjusting an MDO course to a distance learning mode.
In order to efficiently design and deliver customized products, it is crucial that the process of translating customer needs to engineering characteristics and into unique products is smooth and without any misinterpretations. The paper proposes a method that combines design optimization with value-driven design to support and automate configuration of customized products. The proposed framework is applied to a case example with spiral staircases, a product that is uniquely configured for each customer from a set of both standard and customized components; a process that is complex, iterative and error-prone. In the case example, the optimization and value-driven design models are used to automate and speed-up the process of delivering quotations and design proposals that could be judged based on both engineering characteristics as well as their added value, thereby increasing the knowledge at the sales stage. Finally, a multi-objective optimization algorithm is employed to generate a set of Pareto-optimal solutions that contain four clusters of solutions that dominate the baseline design. Hence the decision-maker is given a set of optimal solutions to choose from when balancing different economical and technical characteristics.
An efficient general arrangement is a cornerstone of a good ship design. A big part of the whole general arrangement process is finding an optimized compartment layout. This task is especially tricky since the multiple needs are often conflicting, and it becomes a serious challenge for the ship designers. To aid the ship designers, improved and reliable statistical and computation methods have come to the fore. Genetic algorithms are one of the most widely used methods. Islier's algorithm for the multi-facility layout problem and an improved genetic algorithm for the ship layout design problem are discussed. A new, hybrid genetic algorithm incorporating local search technique to further the improved genetic algorithm's practicality is proposed. Further comparisons are drawn between these algorithms based on a test case layout. Finally, the developed hybrid algorithm is implemented on a section of an actual ship, and the findings are presented.
Integrated Natural Resource Conservation and Development (INRCD) Projects are efforts at worldwide locations to promote economic development of local communities consistent with conservation of natural resources. This umbrella term includes Integration Conservation and Development Projects (ICDPs) introduced by the World Wide Fund to combine social development and conservation s through the use of socio-economic investments, and the Integrated Natural Resource Management (INRM) research and development efforts that have employed a systems approach for quantitative modeling and optimization. In the spirit of the INRCD framework, we describe the development of a system-level agriculture and energy model comprising engineering and economic models for crop, irrigation, and energy subsystem designs for a community in Central Uganda. The model architecture is modular allowing modifications for different system configurations and project locations. We include some initial results and discuss next steps for system optimization, refining model assumptions, and modeling community social benefits as drivers of such projects.
The integration of users' perception in the design process is and important challenge for the optimization of products. This study describes how design recommendations can be drawn, from a perceptual experiment with a panel of subjects using a multi-objective interactive genetic algorithm (IGA). The application concerns the bi-objective optimization of the unpleasantness and the detectability of sounds for electric vehicles (EV). After a description of the experimental protocol for the assessment of the detectability and the unpleasantness of EV sounds (listening test), a set of optimal sounds (Pareto efficient) is defined with an IGA experiment. The analysis of these sounds, based on a probabilistic analysis of the selection process, leads to the definition of design recommendations. A second listening test, involving recommended sounds but also other design proposals, allows an evaluation of the validity of the approach. Results show that the sounds recommended obtain interesting performance, in particular to improve the detectability of EV sounds.
Within this paper, a new method for the quality refinement of external metric standard threads on 3Dprinted bolts is presented. The repair method is based on the application of thread rolling technology, which is applied in terms of cold forming after the regular printing has been finished. The explorative study proves, that the investigated technology has a good potential to solve known precision issues in FDM 3D printing regarding the required accuracy for function fulfilling standardized threads. The application of thread rolling can be done manually and with minimal tool effort, which makes the technology particularly attractive for low cost applications.
Increasing product complexity and individual customer requirements make the design of optimal product families difficult. Numerical optimization supports optimal design but must deal with the following challenges: many design variables, non-linear or discrete dependencies, and many possibilities of assigning shared components to products. Existing approaches use simplifications to alleviate those challenges. However, for use in industrial practice, they often use irrelevant commonality metrics, do not rely on the actual design variables of the product, or are unable to treat discrete variables. We present a two-level approach: (1) a genetic algorithm (GA) to find the best commonality scheme (i.e., assignment scheme of shared components to products) and (2) a particle swarm optimization (PSO) to optimize the design variables for one specific commonality scheme. It measures total cost, comprising manufacturing costs, economies of scales and complexity costs. The approach was applied to a product family consisting of five water hose boxes, each of them being subject to individual technical requirements. The results are discussed in the context of the product family design process.