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1 – 10 of 184M. Neumayer, T. Suppan, T. Bretterklieber, H. Wegleiter and Colin Fox
Nonlinear solution approaches for inverse problems require fast simulation techniques for the underlying sensing problem. In this work, the authors investigate finite element (FE…
Abstract
Purpose
Nonlinear solution approaches for inverse problems require fast simulation techniques for the underlying sensing problem. In this work, the authors investigate finite element (FE) based sensor simulations for the inverse problem of electrical capacitance tomography. Two known computational bottlenecks are the assembly of the FE equation system as well as the computation of the Jacobian. Here, existing computation techniques like adjoint field approaches require additional simulations. This paper aims to present fast numerical techniques for the sensor simulation and computations with the Jacobian matrix.
Design/methodology/approach
For the FE equation system, a solution strategy based on Green’s functions is derived. Its relation to the solution of a standard FE formulation is discussed. A fast stiffness matrix assembly based on an eigenvector decomposition is shown. Based on the properties of the Green’s functions, Jacobian operations are derived, which allow the computation of matrix vector products with the Jacobian for free, i.e. no additional solves are required. This is demonstrated by a Broyden–Fletcher–Goldfarb–Shanno-based image reconstruction algorithm.
Findings
MATLAB-based time measurements of the new methods show a significant acceleration for all calculation steps compared to reference implementations with standard methods. E.g. for the Jacobian operations, improvement factors of well over 100 could be found.
Originality/value
The paper shows new methods for solving known computational tasks for solving inverse problems. A particular advantage is the coherent derivation and elaboration of the results. The approaches can also be applicable to other inverse problems.
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The purpose of this paper is to investigate the vehicle-based sensor effect and pavement temperature on road condition assessment, as well as to compute a threshold value for the…
Abstract
Purpose
The purpose of this paper is to investigate the vehicle-based sensor effect and pavement temperature on road condition assessment, as well as to compute a threshold value for the classification of pavement conditions.
Design/methodology/approach
Four sensors were placed on the vehicle’s control arms and one inside the vehicle to collect vibration acceleration data for analysis. The Analysis of Variance (ANOVA) tests were performed to diagnose the effect of the vehicle-based sensors’ placement in the field. To classify road conditions and identify pavement distress (point of interest), the probability distribution was applied based on the magnitude values of vibration data.
Findings
Results from ANOVA indicate that pavement sensing patterns from the sensors placed on the front control arms were statistically significant, and there is no difference between the sensors placed on the same side of the vehicle (e.g., left or right side). A reference threshold (i.e., 1.7 g) was computed from the distribution fitting method to classify road conditions and identify the road distress based on the magnitude values that combine all acceleration along three axes. In addition, the pavement temperature was found to be highly correlated with the sensing patterns, which is noteworthy for future projects.
Originality/value
The paper investigates the effect of pavement sensors’ placement in assessing road conditions, emphasizing the implications for future road condition assessment projects. A threshold value for classifying road conditions was proposed and applied in class assignments (I-17 highway projects).
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Yanmin Zhou, Zheng Yan, Ye Yang, Zhipeng Wang, Ping Lu, Philip F. Yuan and Bin He
Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing…
Abstract
Purpose
Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.
Design/methodology/approach
This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.
Findings
This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.
Originality/value
The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.
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Serena Summa, Alex Mircoli, Domenico Potena, Giulia Ulpiani, Claudia Diamantini and Costanzo Di Perna
Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with…
Abstract
Purpose
Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations
Design/methodology/approach
The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.
Findings
The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.
Originality/value
This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.
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Armando Di Meglio, Nicola Massarotti and Perumal Nithiarasu
In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the…
Abstract
Purpose
In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.
Design/methodology/approach
To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.
Findings
The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.
Originality/value
The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.
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Jonas Ekow Yankah, Kofi Owusu Adjei and Chris Kurbom Tieru
Robotics and automation are successful in construction, health and safety, but costs and expertise hinder their use in developing nations. This study examined mobile apps as a…
Abstract
Purpose
Robotics and automation are successful in construction, health and safety, but costs and expertise hinder their use in developing nations. This study examined mobile apps as a more accessible and affordable alternative.
Design/methodology/approach
This descriptive study explored the use of mobile apps in construction, health and safety management. It used a literature review to identify their availability, accessibility, and capabilities. The study consisted of four five stages: searching for relevant apps, selecting them based on versatility, examining their specific functions, removing untested apps and discussing their functions based on empirical studies.
Findings
A comprehensive literature review identified 35 mobile apps that are relevant to health and safety management during construction. After rigorous analysis, eight apps were selected for further study based on their relevance, user friendliness and compliance with safety standards. These apps collectively serve 28 distinct functions, including first-aid training and administration, safety compliance and danger awareness, safety education and training, hazard detection and warnings.
Practical implications
This study suggests that mobile apps can provide a cost-effective and readily accessible alternative to robotics and automation in health and safety management in construction. Further research is needed to accurately assess the efficacy of these apps in real-world conditions.
Originality/value
This study explored the use of apps in health and safety management, highlighting their diverse capabilities and providing a framework for project managers, contractors and safety officers to select suitable apps.
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Pietro Miglioranza, Andrea Scanu, Giuseppe Simionato, Nicholas Sinigaglia and America Califano
Climate-induced damage is a pressing problem for the preservation of cultural properties. Their physical deterioration is often the cumulative effect of different environmental…
Abstract
Purpose
Climate-induced damage is a pressing problem for the preservation of cultural properties. Their physical deterioration is often the cumulative effect of different environmental hazards of variable intensity. Among these, fluctuations of temperature and relative humidity may cause nonrecoverable physical changes in building envelopes and artifacts made of hygroscopic materials, such as wood. Microclimatic fluctuations may be caused by several factors, including the presence of many visitors within the historical building. Within this framework, the current work is focused on detecting events taking place in two Norwegian stave churches, by identifying the fluctuations in temperature and relative humidity caused by the presence of people attending the public events.
Design/methodology/approach
The identification of such fluctuations and, so, of the presence of people within the churches has been carried out through three different methods. The first is an unsupervised clustering algorithm here termed “density peak,” the second is a supervised deep learning model based on a standard convolutional neural network (CNN) and the third is a novel ad hoc engineering feature approach “unexpected mixing ratio (UMR) peak.”
Findings
While the first two methods may have some instabilities (in terms of precision, recall and normal mutual information [NMI]), the last one shows a promising performance in the detection of microclimatic fluctuations induced by the presence of visitors.
Originality/value
The novelty of this work stands in using both well-established and in-house ad hoc machine learning algorithms in the field of heritage science, proving that these smart approaches could be of extreme usefulness and could lead to quick data analyses, if used properly.
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Klára Rybenská, Lenka Knapová, Kamil Janiš, Jitka Kühnová, Richard Cimler and Steriani Elavsky
A wide gap exists between the innovation and development of self-monitoring, analysis and reporting technology (SMART) technologies and the actual adoption by older adults or…
Abstract
Purpose
A wide gap exists between the innovation and development of self-monitoring, analysis and reporting technology (SMART) technologies and the actual adoption by older adults or those caring for them. This paper aims to increase awareness of available technologies and describes their suitability for older adults with different needs. SMART technologies are intelligent devices and systems that enable autonomous monitoring of their status, data analysis or direct feedback provision.
Design/methodology/approach
This is a scoping review of SMART technologies used and marketed to older adults or for providing care.
Findings
Five categories of SMART technologies were identified: (1) wearable technologies and smart tools of daily living; (2) noninvasive/unobtrusive technology (i.e. passive technologies monitoring the environment, health and behavior); (3) complex SMART systems; (4) interactive technologies; (5) assistive and rehabilitation devices. Technologies were then linked with needs related to everyday practical tasks (mainly applications supporting autonomous, independent living), social and emotional support, health monitoring/managing and compensatory assistance rehabilitation.
Research limitations/implications
When developing, testing or implementing technologies for older adults, researchers should clearly identify concrete needs these technologies help meet to underscore their usefulness.
Practical implications
Older adults and caregivers should weigh the pros and cons of different technologies and consider the key needs of older adults before investing in any tech solution.
Social implications
SMART technologies meeting older adult needs help support both independent, autonomous life for as long as possible as well as aiding in the transition to assisted or institutionalized care.
Originality/value
This is the first review to explicitly link existing SMART technologies with the concrete needs of older adults, serving as a useful guide for both older adults and caregivers in terms of available technology solutions.
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Robin Ayers Frkal and Michael S. Lewis
This study explores the work practices of managers who increased working from home during the pandemic to determine what, if any, impact there was on the conditions for vertical…
Abstract
Purpose
This study explores the work practices of managers who increased working from home during the pandemic to determine what, if any, impact there was on the conditions for vertical leadership development.
Design/methodology/approach
The project utilized a survey approach. Each of the participants completed an anonymous online questionnaire using Google Forms. The questionnaire included four sections. The first section included informed consent and required participants to agree before completing the questionnaire. Participants provided general demographic information in the second section, including gender, age, race, job title, company size, average project team size and industry. The third section asked if there had been any change in their work location following the pandemic. The last section asked participants about their work practices.
Findings
This study demonstrates that managers continued to be engaged in vertical leadership development activities while working from home. It also suggests that managers faced challenges working from home following the COVID-19 pandemic, which were prime vertical leadership development opportunities.
Originality/value
To capitalize on these opportunities, organizations can more intentionally support the development of their remote staff.
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Guanchen Liu, Dongdong Xu, Zifu Shen, Hongjie Xu and Liang Ding
As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous…
Abstract
Purpose
As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.
Design/methodology/approach
Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.
Findings
In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.
Originality/value
With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.
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