Hasil untuk "Engineering economy"

Trevor Zink, R. Geyer

S. Sauvé, Sophie Bernard, P. Sloan

Abstract The intermeshing of disciplines from the natural sciences, social sciences, engineering and management has become essential to addressing today's environmental challenges. Yet, this can be a daunting task because experts from different disciplines may conceptualize the problems in very different ways and use vocabularies that may not be well understood by one another. This paper explores three alternative environmental concepts used in transdisciplinary research, and outlines some of the epistemological and practical problems that each one poses. It pays particular attention to the increasingly popular concept of “circular economy”, and contrasts it with the more commonly-used concepts of “environmental sciences” and “sustainable development”. In clarifying the nature, meaning and inter-relationship of these alternative concepts, the paper helps trans-disciplinary researchers to understand the opportunities and challenges associated with each one.

Beatriz C. Guerra, Fernanda Leite

Abstract Increasing environmental concerns and resource scarcity risks have drawn attention to a Circular Economic (CE) model during the last decade. Nevertheless, literature related to the state of practice of CE in the built environment in the United States (U.S.) is still limited. In this context, this study investigates U.S. architectural, engineering, and construction (AEC) industry stakeholders’ awareness of CE. The investigation also covers major barriers for the implementation of strategies aligned to the CE model, and enabling factors for a transition from a linear economic model to a CE model in the construction industry in the U.S. A mixed-methods approach was deployed through a combination of online survey and interviews with AEC industry stakeholders from different regions of the U.S. Results revealed that some strategies are widely disseminated (i.e., open-loop recycling, selective demolition, and prefabrication), whereas others are hardly adopted (i.e., design for disassembly, design in layers, closed-loop recycling). Additionally, findings indicate budget and upfront costs, project schedule and timeline, lack of awareness and regulations, and current business models as major barriers for the implementation of strategies aligned to a CE model. Furthermore, four enabling factors for a transition to a CE model in the construction industry were identified (i.e., education and cultural change, data availability, policies and incentives, and novel voluntary stewardships). Notably, contributions of this study include fostering a much needed debate around circular construction and its challenges, and expanding the limited existing body of knowledge.

Venkateshwaran Venkatachalam, Sebastian Spierling, Mikołaj Owsianiak et al.

ABSTRACT In 2015, the United Nations introduced the 17 Sustainable Development Goals (SDGs) to address major global challenges in sustainable development. Different industrial sectors are held accountable by their stakeholders for how their actions can contribute to achieving these goals. Among others, the plastic sector has come under scrutiny due to its linearity, characterized by low recovery rates after use and adverse effects on the environment resulting from uncontrolled disposal. Therefore, focus should be given not only to improving production processes and developing regulatory frameworks to manage plastic wastes but also to product design, as composition and construction determine whether products can be effectively recovered and recycled after use. Ecodesign is an approach that seeks to integrate different environmental considerations as early as during the design phase by focusing on the entire lifecycle of a product. To understand how plastics influence various dimensions of sustainability, a systematic literature review was conducted to examine the impact of plastics across different indicators of SDGs and their relationship to different ecodesign strategies. Based on the findings of the review, this study aims to identify plastic‐specific ecodesign strategies that can enhance resource efficiency and material recoverability. Furthermore, to compare and quantify these ecodesign strategies, a new methodological framework is proposed.

David J. Langley, Eugenia Rosco, Marios Angelopoulos et al.

In order for firms to implement the Circular Economy, and close all material and energy cycles, connections are needed not only within but also between multiple Industrial Ecosystems. To enable such complex interconnections, the European Union is preparing legislation to enforce the use of digital product passports (DPPs). These are verifiable collections of data about products ’ composition, environmental footprint and opportunities for preventing waste. The notion of the DPP relies heavily on a suitable digital infrastructure, and it opens the possibility of using the power of artificial intelligence (AI), to optimize circular production within and between Industrial Ecosystems. The benefits of DPPs will only be attained if their design, knowledge engineering, and implementation is well-orchestrated. The purpose of this paper is to develop a set of guiding principles for the orchestration of DPPs, based upon a trans -disciplinary analysis, that form a theoretical basis upon which future research can build.

Cunying Zhang, Wenbo Bie, Yu Liu et al.

Good machining performance and high surface quality can be achieved in engineering compound materials when subjected to ultrasonic vibration machining systems. This study established an ultrasonic vibration system with a complex disk tool. The finite element simulation model of the complex disk tool was created using ANSYS software. Modal analysis was utilized to obtain the disk’s resonance frequency and other parameters. Based on the local resonance characteristics of the system and the simulation results, the horn, transducers, and other components were designed. The node position of the compound ultrasound system can be accurately determined, leading to the acquisition of a cutting disc with a disc-shaped cutting edge that exhibits equal center distance and amplitude longitudinal vibration in the ultrasonic vibration system. This vibration system conforms to the local resonance theory of slender rods. A theoretical method for calculating the nodes of the ultrasonic vibration system with a discoid non-resonant frequency was developed. A slight deviation between the measured resonance frequency of the system and the theoretical results was observed. Thus, a reliable design method for ultrasonic vibration cutting systems with complex disk tools has been provided.

ZENG Zhuo, ZHENG Honggang, XIANG Sheng et al.

As the bridge construction goes forward to the deep-water environments, the permanent floating bridge structures have attracted more and more attention from international scholars. The project cases of worldwide representative permanent floating bridges were presented. The structural systems of the built permanent floating bridges were summarized. The research and application advances regarding the mechanical features, the construction process, and the special configurations of the permanent floating bridges were introduced. Finally, from the perspectives of the engineering economy and environment applicability, the development prospect of permanent floating bridges was analyzed. The research shows that the permanent floating bridge structure has been applied in engineering around the world and has two types of structural systems, which are the continuous pontoon system and the discrete pontoon system. The permanent floating bridges adopted in deep-water environments have shown superior engineering economy. Based on further research and verifications, the permanent floating bridge structures can be applied in deep-water crossing projects.

Johannes Welsch, Silke Schicktanz

BackgroundIntelligent assistive technologies (IAT) have become more common in dementia care. Ethical reflection on technology-assisted dementia care (TADC) has focused so far mainly on individual and interpersonal implications (e.g., self-determination, (in)dependence, safety or privacy issues, caregivers’ support and cost-efficiency). From an empowerment-sensitive perspective, however, the societal, political, economic and technological preconditions for TADC should be more deeply analyzed in terms of their accelerating or inhibiting effects on technology development, implementation and usage. Therefore, the aim of this study was to explore these preconditions in the German context and so to contribute to more empowerment-sensitive structures.MethodsSemi-structured interviews were conducted with 20 German-speaking experts from health care, health policy and the fields contributing to IAT (e.g., computer science, engineering). Thematic content analysis was used to analyze the data.FindingsThe experts’ assessments of the current preconditions for TADC in Germany were starkly ambivalent. In the field of „society”, they identified digitalization, a change in mentality towards IAT and demographic change as accelerators, unequally distributed digital literacy, misleading perceptions and a lack of affinity as inhibitors. In the field “politics - regulation - economy”, experts identified scarcity of public resources, growing private wealth and regulatory progress as accelerators and unclear financing options, an uncertain market, data protection and ethical challenges as inhibitors. In the field “technology”, they identified progress in basic technical research and improved customizability and interconnectivity as accelerators, while deficient digital infrastructure, a lack of user participation, dementia-specific challenges and challenges regarding data collection and security were seen as inhibitors.ConclusionsTADC promises an empowerment of persons with dementia, e.g. by enhancing their self-determination, increasing their independence from social control and by allowing more social participation. Yet its societal, political, economic and technological environments preconfigure the likelihood of successful empowerment as a socio-technical practice within TADC. Accelerators in the fields of society, politics-regulation-economy and technology need to be consolidated and strengthened. Inhibitors need to be mitigated, e.g. by with new educational, political and market economic policies. We make policy recommendations based on these conclusions.

Timo Kehrer, Robert Haines, Guido Juckeland et al.

Anecdotal evidence suggests that Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) often use different terminologies for similar concepts, creating communication challenges. To better understand these divergences, we have started investigating how SE fundamentals from the SER community are interpreted within the RSE community, identifying aligned concepts, knowledge gaps, and areas for potential adaptation. Our preliminary findings reveal opportunities for mutual learning and collaboration, and our systematic methodology for terminology mapping provides a foundation for a crowd-sourced extension and validation in the future.

Lekshmi Murali Rani, Richard Berntsson Svensson, Robert Feldt

The integration of AI for Requirements Engineering (RE) presents significant benefits but also poses real challenges. Although RE is fundamental to software engineering, limited research has examined AI adoption in RE. We surveyed 55 software practitioners to map AI usage across four RE phases: Elicitation, Analysis, Specification, and Validation, and four approaches for decision making: human-only decisions, AI validation, Human AI Collaboration (HAIC), and full AI automation. Participants also shared their perceptions, challenges, and opportunities when applying AI for RE tasks. Our data show that 58.2% of respondents already use AI in RE, and 69.1% view its impact as positive or very positive. HAIC dominates practice, accounting for 54.4% of all RE techniques, while full AI automation remains minimal at 5.4%. Passive AI validation (4.4 to 6.2%) lags even further behind, indicating that practitioners value AI's active support over passive oversight. These findings suggest that AI is most effective when positioned as a collaborative partner rather than a replacement for human expertise. It also highlights the need for RE-specific HAIC frameworks along with robust and responsible AI governance as AI adoption in RE grows.

Daniel Mendez, Paris Avgeriou, Marcos Kalinowski et al.

Empirical Software Engineering has received much attention in recent years and became a de-facto standard for scientific practice in Software Engineering. However, while extensive guidelines are nowadays available for designing, conducting, reporting, and reviewing empirical studies, similar attention has not yet been paid to teaching empirical software engineering. Closing this gap is the scope of this edited book. In the following editorial introduction, we, the editors, set the foundation by laying out the larger context of the discipline for a positioning of the remainder of this book.

Kevin Hermann, Sven Peldszus, Jan-Philipp Steghöfer et al.

Software security is of utmost importance for most software systems. Developers must systematically select, plan, design, implement, and especially, maintain and evolve security features -- functionalities to mitigate attacks or protect personal data such as cryptography or access control -- to ensure the security of their software. Although security features are usually available in libraries, integrating security features requires writing and maintaining additional security-critical code. While there have been studies on the use of such libraries, surprisingly little is known about how developers engineer security features, how they select what security features to implement and which ones may require custom implementation, and the implications for maintenance. As a result, we currently rely on assumptions that are largely based on common sense or individual examples. However, to provide them with effective solutions, researchers need hard empirical data to understand what practitioners need and how they view security -- data that we currently lack. To fill this gap, we contribute an exploratory study with 26 knowledgeable industrial participants. We study how security features of software systems are selected and engineered in practice, what their code-level characteristics are, and what challenges practitioners face. Based on the empirical data gathered, we provide insights into engineering practices and validate four common assumptions.

Tim Aebersold, Soheyl Massoudi, Mark D. Fuge

Engineering complex systems (aircraft, buildings, vehicles) requires accounting for geometric and performance couplings across subsystems. As generative models proliferate for specialized domains (wings, structures, engines), a key research gap is how to coordinate frozen, pre-trained submodels to generate full-system designs that are feasible, diverse, and high-performing. We introduce Generative Latent Unification of Expertise-Informed Engineering Models (GLUE), which orchestrates pre-trained, frozen subsystem generators while enforcing system-level feasibility, optimality, and diversity. We propose and benchmark (i) data-driven GLUE models trained on pre-generated system-level designs and (ii) a data-free GLUE model trained online on a differentiable geometry layer. On a UAV design problem with five coupling constraints, we find that data-driven approaches yield diverse, high-performing designs but require large datasets to satisfy constraints reliably. The data-free approach is competitive with Bayesian optimization and gradient-based optimization in performance and feasibility while training a full generative model in only 10 min on a RTX 4090 GPU, requiring more than two orders of magnitude fewer geometry evaluations and FLOPs than the data-driven method. Ablations focused on data-free training show that subsystem output continuity affects coordination, and equality constraints can trigger mode collapse unless mitigated. By integrating unmodified, domain-informed submodels into a modular generative workflow, this work provides a viable path for scaling generative design to complex, real-world engineering systems.

U. Uwuigbe, Osman Issah, Uwuigbe Olubukunola Ranti et al.

The study “Circular Economy: A Bibliometric Review of Research in Emerging Economies” examines the growing literature on circular economy practices, particularly within environmental science, business, management, and engineering. Utilizing a bibliometric tool and quantitative approach, the research analyzed patterns and trends in publications on circular economy research in emerging economies from 2010 to 2024. The study observed a notable increase in publications since 2019, reflecting a global shift towards sustainable development and heightened awareness of circular economy principles in emerging economies. Key themes identified include sustainability, waste management, and innovative business models, highlighting efforts to address implementation challenges. The significant contributions from countries like India, the UK, and China, along with strong collaborative networks, underscore the importance of international partnerships. The study suggests that future research should strengthen interdisciplinary collaboration and incorporate regional and local contexts to develop tailored strategies. Furthermore, it emphasizes the need for expanded global cooperation.

M. Bertagni, R. Socolow, J. M. Martirez et al.

Significance The global transition to low-carbon energy necessitates exploring alternatives to fossil fuels. Hydrogen has emerged as a promising option; however, hydrogen storage and transportation challenges have led to considering ammonia as a hydrogen carrier and fuel. This study investigates the potential environmental risks associated with ammonia use in the energy sector. Our findings demonstrate that reactive nitrogen compounds released throughout the ammonia value chain can harm air quality, human health, ecosystems, and climate, and lead to stratospheric ozone depletion. However, we also show that optimal engineering practices and management strategies can effectively mitigate these concerns. Our research contributes to informed decision-making and the development of environmentally responsible ammonia energy systems.

Bo Zhang, Weili Chen, Chaoming Xu et al.

This paper proposes an evaluating and mapping methodology of terrain traversability for off-road navigation of autonomous vehicles in unstructured environments. Terrain features are extracted from RGB images and 3D point clouds to create a traversal cost map. The cost map is then employed to plan safe trajectories. Bayesian generalized kernel inference is employed to assess unknown grid attributes due to the sparse raw point cloud data. A Kalman filter also creates density local elevation maps in real time by fusing multiframe information. Consequently, the terrain semantic mapping procedure considers the uncertainty of semantic segmentation and the impact of sensor noise. A Bayesian filter is used to update the surface semantic information in a probabilistic manner. Ultimately, the elevation map is utilized to extract geometric characteristics, which are then integrated with the probabilistic semantic map. This combined map is then used in conjunction with the extended motion primitive planner to plan the most effective trajectory. The experimental results demonstrate that the autonomous vehicles obtain a success rate enhancement ranging from 4.4% to 13.6% and a decrease in trajectory roughness ranging from 5.1% to 35.8% when compared with the most developed outdoor navigation algorithms. Additionally, the autonomous vehicles maintain a terrain surface selection accuracy of over 85% during the navigation process.

Aristotelis C. Tagarakis, Lefteris Benos, George Kyriakarakos et al.

Digital twins aim to optimize practices implemented in various sectors by bridging the gap between the physical and digital worlds. Focusing on open-field agriculture, livestock farming, and forestry and reviewing the current applications in these domains, this paper reveals the multifaceted roles of digital twins. Diverse key aspects are examined, including digital twin integration and maturity level, means of data acquisition, technological capabilities, and commonly used input and output features. Through the prism of four primary research questions, the state of the art of digital twins, the extent of their achieved integration, and an overview of the critical issues and potential advancements are provided in the landscape of the sectors under consideration. The paper concludes that in spite of the remarkable progress, there is a long way towards achieving full digital twin. Challenges still persist, while the key factor seems to be the integration of expert knowledge from different stakeholders. In light of the constraints identified in the review analysis, a new sector-specific definition for digital twins is also suggested to align with the distinctive characteristics of intricate biotic and abiotic systems. This research is anticipated to serve as a useful reference for stakeholders, enhancing awareness of the considerable benefits associated with digital twins and promoting a more systematic and comprehensive exploration of this transformative topic.

Yongting Feng, Meijuan Xu, Dongwei Chen et al.

Physical techniques are widely applied in the food industry due to their positive impact on food quality and the environment. Temperature differences can effectively modify starch, but the resulting changes in starch structure and quality remain unclear. In this study, the corn starch was processed with high temperature, low temperature, and temperature difference (TD), including high temperature before low temperature (H-L) and low temperature before high temperature (L-H). The results showed that high temperature induced the umbilicus to concave inward shape and sharply decreased the amylose content, while low temperature increased the surface micropores and reduced the A-chain. TD reduced the fluorescence intensity and increased the clearness of the growth ring. TD elevated the relative crystallinity (RC), short-range order, A/B₁ chains, hydrolysis parameters, and resistant starch (RS), and reduced amylose content, B₂/B₃ chains, and viscosity. Moreover, the corn starches treated by H-L had lower amylose content and higher RC, 1047/1022, A-chain, and RS than those treated by L-H. Overall, high temperature degraded the amylose and low temperature destroyed the amylopectin. During the TD, H-L can accelerate the starch molecular rearrangement more than the opposite temperature treatment order. These results will help produce novel starches for better food applications.

Юрій Полупан, Ольга Малєєва

Предметом дослідження статті є процеси прийняття рішень з удосконалення елементів логістичного ланцюга (процесів постачання та збуту) виробничого підприємства в умовах невизначеності та ризиків. Мета роботи – зменшення часу й вартості постачання та збуту продукції виробничого підприємства з огляду на можливі ризики за допомогою прийняття раціональних управлінських рішень. У статті розв’язуються такі завдання: розгляд особливостей елементів логістичного ланцюга; дослідження основних проблем постачання та збуту й визначення способів їх вирішення; розроблення системної моделі логістичних ризиків виробничого підприємства; формування дерев альтернативних рішень у стратегічному управлінні ланцюгом постачання на виробничих підприємствах. Упроваджуються такі методи: системний підхід, методи структурної декомпозиції, ризик-орієнтований підхід. Досягнуто таких результатів: розглянуто особливості та виокремлено проблеми елементів логістичного ланцюга (постачання, виробництво, складування та збут); досліджено основні завдання управління ланцюгом постачання та визначено способи їх виконання; окреслено проблеми складського управління; ідентифіковано внутрішні та зовнішні ризики постачання; сформовано системну модель логістичних ризиків виробничого підприємства, основними складниками якої є логістичні проблеми, часткові ризики, їх наслідки та можливі управлінські рішення з парирування ризиків; побудовано дерева рішень для визначених проблем нестабільності постачання сировини й транспортних заторів і затримань; побудовано діаграму альтернативних рішень для ілюстративного прикладу. Висновки. Для подолання проблеми нестабільності постачання сировини рекомендується розвивати диверсифікацію джерел постачання, резервування запасів та використання альтернативних транспортних маршрутів. Побудова альтернативних дерев рішень у стратегічному управлінні є ефективним інструментом прийняття раціональних рішень виробничим підприємством у складних умовах невизначеності та ризиків. Вони допомагають аналізувати альтернативи та їх наслідки, щоб обрати спосіб оптимізації логістичного ланцюга.

Shiwei Liu, Chun-ao Wei, Miaoxin Li et al.

Abstract This work explores the extraction of the spatial distribution and chemical composition information of pigments in colored relics through visible spectral images. An adaptive superpixel segmentation method is proposed to extract the spatial distribution information of pigments. Quadtree decomposition is applied to generate nonuniform initial seed points based on the image homogeneity. These seed points are used as the initial cluster centers in an extended simple linear iterative clustering (SLIC) algorithm for visible spectral images to create superpixels of varying sizes that reflect the homogeneity. Each superpixel is subsequently treated as an individual area in the colored relics, and a pigment identification method based on the visible spectral reflectance is proposed to identify the pigments in these areas. A standard reference database is constructed using samples that simulate the painting process of ancient wall paintings in the Mogao Grottoes. Geometric features, which are characterized by the linear combination of the normalized visible spectral reflectance, its slope and its curvature, are designed to represent the chemical composition of pigments. The geometric features of the superpixels are compared with those of the pigments in the database using the Euclidean distance to determine the pigments in each area of the colored relics. This work is expected to provide scientific guidance for pigment selection in the color restoration of colored relics.