Hasil untuk "Engineering (General). Civil engineering (General)"

Jun Zhang, Chuan Zhang, Mingtao Zhang

ABSTRACT This study integrates embodied intelligence (EI) with a two‐stage two‐sided Hotelling duopoly model to reveal how physical intelligence reshapes digital platform equilibrium in intelligent logistics. By embedding EI‐driven efficiency parameters into market cost functions, the model demonstrates that improved perception and coordination reduce the effective transportation cost and transform pricing dynamics between competing platforms. Experiments in a digital twin warehouse show that when EI strength η increases from 0 to 0.6, throughput rises by 37.5%, Dock‐to‐Stock time decreases by 30.9%, and unit energy consumption drops by 7%–8%, verifying that EI directly enhances operational and economic efficiency. Further analysis confirms that asymmetric advantages in action or data lead to discriminatory pricing as the optimal strategy. Complementary encryption experiments indicate that lightweight security algorithms such as SHA‐1/SHA‐256 add less than 3% latency overhead, maintaining real‐time performance.

Somporn Sahachaiseree, Takashi Oguchi

ABSTRACT Reinforcement learning (RL) is a promising machine‐learning solution to traffic signal control problems, which have been extensively studied. However, variants of non‐linear, deep artificial neural network (ANN) function approximators (FAs) have been predominantly employed in previous studies proposing RL‐based controllers, leaving a significant interpretability issue due to their black‐box nature. In this work, the use of the linear FA for a value‐based RL agent in traffic signal control problems is investigated along with the least‐squares Q‐learning method, abbreviated as LSTDQ. The interpretable linear FA was found to be adequate for the RL agent to learn an optimal policy. This leads to the proposal to replace a non‐linear ANN FA with the linear FA counterpart, resolving the interpretability issue. Moreover, the LSTDQ learning method shows superior behaviour convergence compared to a gradient descent method. In a low‐intensity arrival pattern scenario, the control by the RL agent cuts about half of the average delay resulting from the pretimed control. Owing to the conciseness of the linear FA, a direct interpretation analysis of the converged linear‐FA parameters is presented. Lastly, two online relearning tests of the agents under non‐stationary arrivals are conducted to demonstrate the online performance of LSTDQ. In conclusion, the linear‐FA specification and the LSTDQ method are together proposed to be used for its control algorithm interpretability property, superior convergence quality, and lack of hyperparameters.

C. J. Horwell, S. Ravenhall, R. Clarkson et al.

Abstract Volcanic eruptions produce plumes of ash, gas and aerosols that present a risk to aviation at all standard flight levels. Here, we investigate atmospheric dispersal of volcanic emissions, whether and how they infiltrate aircraft, and whether ground-level public health exposure thresholds can be related to the pressurised cabin environment. We then review the limited evidence for physical and mental health, and behavioural impacts, resulting from volcanic emissions entering aircraft. Serious health risks are considered low for healthy individuals, but respiratory irritation is likely for a high exposure scenario to sulfur dioxide (SO2). Asthmatics are particularly sensitive to SO2, with even relatively low, short exposures, potentially resulting in severe respiratory impacts. Negative group behaviours are not expected but individual distress is possible. Communicating this evidence to the aviation industry may result in more informed decision-making on flightpath alterations and triggering of emergency protocols, both before and during volcanic emission encounters.

Pengqiang Yu, Kejia Wu, Dongsheng Li et al.

This paper introduces an analytical method for passive earth pressure calculation based on a rigorous stress field analysis within the sliding wedge. Unlike traditional horizontal layer methods, this approach directly solves for the stress state at any point within the wedge by analyzing the equilibrium of 2D differential soil elements under appropriate boundary conditions, eliminating the need for a priori assumptions about the soil arch shape. The method yields the passive earth pressure distribution on the retaining structure and derives the soil arch shape analytically from major principal stress trajectories. This derived arch shape differs notably from conventional circular or parabolic assumptions, especially at higher soil–wall friction angles. Parametric studies show that the passive earth pressure coefficient increases with internal friction angle and surcharge. However, a key finding is the non-monotonic dependence of the passive earth pressure coefficient on the soil–wall friction angle, contrasting with many existing theories. Comparisons show predictions by the proposed method align well with experimental data, particularly offering a better representation of pressure distributions in the lower regions of retaining walls compared to Coulomb theory and other existing methods.

Liu Hui quan, Wang Yu, Lu Hao

Coal dust deposition in boiler tail gas pipelines can significantly affect boilers’ thermal and energy efficiency. This study investigates the deposition characteristics of coal dust particles in boiler tail gas tubes in variable cross-section tubes. Numerical simulations were performed using the Reynolds Stress Model and the Discrete Particle Model. User-defined functions coding is used to construct the particle deposition model in the particle deposition model. The study analyses the distribution of turbulent kinetic energy locations in the gradient tube, compares the distribution of particle deposition on its wall, and concludes that the deposition distribution of coal dust particles in the gradient tube is slightly different for different particle sizes. Smaller particles have a higher deposition efficiency in equal cross-section pipes than larger particles. Particle size also has a significant effect on pipe taper and expansion. The results of this study can provide theoretical guidance for optimising the design of boiler tail gas pipelines, improving energy efficiency, and reducing environmental pollution.

Wenqiang Liu, Li Yan, Ningning Ma et al.

With the rapid development of deep learning, researchers are actively exploring its applications in the field of industrial anomaly detection. Deep learning methods differ significantly from traditional mathematical modeling approaches, eliminating the need for intricate mathematical derivations and offering greater flexibility. Deep learning technologies have demonstrated outstanding performance in anomaly detection problems and gained widespread recognition. However, when dealing with multivariate data anomaly detection problems, deep learning faces challenges such as large-scale data annotation and handling relationships between complex data variables. To address these challenges, this study proposes an innovative and lightweight deep learning model—the Attention-Based Deep Convolutional Autoencoding Prediction Network (AT-DCAEP). The model consists of a characterization network based on convolutional autoencoders and a prediction network based on attention mechanisms. The AT-DCAEP exhibits excellent performance in multivariate time series data anomaly detection without the need for pre-labeling large-scale datasets, making it an efficient unsupervised anomaly detection method. We extensively tested the performance of AT-DCAEP on six publicly available datasets, and the results show that compared to current state-of-the-art methods, AT-DCAEP demonstrates superior performance, achieving the optimal balance between anomaly detection performance and computational cost.

Jongho Lee, Jiuk Shin, Jaewook Lee et al.

Large fires in factories cause severe human casualties and property damage. Thus, preparing more economical and efficient management strategies for fire prevention can significantly improve fire safety. This study deals with property damage grade prediction by fire based on simplified building information. This paper’s primary objective is to propose and verify a framework for predicting the scale of property damage caused by fire using machine learning (ML). Korean public datasets are collected and preprocessed, and ML algorithms are trained with only 15 input data using building register and fire scenario information. Four models (artificial neural network (ANN), decision tree (DT), k-nearest neighbor (KNN), and random forest (RF)) are used for ML. The RF model is the most suitable for this study, with recall and precision of 74.2% and 73.8%, respectively. Structure, floor, causes, and total floor area are the critical factors that govern the fire size. This study proposes a novel approach by utilizing ML models to accurately and rapidly predict the size of fire damage based on basic building information. By analyzing domestic fire incident data and creating fire scenarios, a similar ML model can be developed.

Malikasab Bagawan, Suresh T. Dundur, Rajesh Gurani et al.

AbstractElastomers are the class of materials that are widely used in a variety of industrial, commercial, and consumer applications due to their unique mechanical properties, including high elasticity, high flexibility, and high resilience. However, there are many challenges in machining of elastomers such as poor surface finish, build up of heat, degradation of elastomers, etc. To overcome these challenges, cryogenic cooling assistance has been introduced as a means of improving the machinability of elastomers. This paper presents a soft computing approach for optimizing the surface roughness and cutting force during turning of elastomers under different lubrication conditions. Three types of elastomers, namely Nitrile Rubber (NBR), Polyurethane Rubber (PU), and Neoprene Rubber (CR), are studied, and a cryogenic fluid delivery system is employed to improve the machining process. Taguchi’s L27 array is used to vary the input parameters, and a Back-Propagation Artificial Neural Network (BPANN) model is developed to predict the cutting force and surface roughness. The cutting force and surface roughness are analyzed under different cooling conditions, cutting speeds, feeds, and depths of cut for various elastomers. The results show that changes in cutting conditions significantly affect the cutting force and that the type of lubrication used affects the cutting force by altering the material’s physical properties. Cutting force is significantly influenced by cutting conditions, and NBR requires the highest cutting force compared to PU and CR. Further, at a cutting speed of 55 m/min, a feed of 0.11 mm/rev, and a depth of cut of 0.25 mm, the cutting force for NBR (85.1 N), while for PU (75.1 N) and CR (80.3 N), respectively. Finally, with LN2 lubrication conditions, the Cutting Force decreased by 45% and Surface Roughness decreased by 16.9%. This study provides insights into the factors affecting the elastomer machining process, which can be useful for optimizing the machining process parameters and improving machining efficiency.

Jeroen C. J. GROOT, Xiaolin YANG

<List> <ListItem><ItemContent><p>● Impacts of 30 cropping systems practiced on the North China Plain were evaluated.</p></ItemContent></ListItem> <ListItem><ItemContent><p>● Trade-offs were assessed among productive, economic and environmental indicators.</p></ItemContent></ListItem> <ListItem><ItemContent><p>● An evolutionary algorithm was used for multi-objective optimization.</p></ItemContent></ListItem> <ListItem><ItemContent><p>● Conflict exists between productivity and profitability versus lower ground water decline.</p></ItemContent></ListItem> <ListItem><ItemContent><p>● Six strategies were identified to jointly mitigate the trade-offs between objectives.</p></ItemContent></ListItem></List></p> <p>Since the Green Revolution cropping systems have been progressively homogenized and intensified with increasing rates of inputs such as fertilizers, pesticides and water. This has resulted in higher crop productivity but also a high environmental burden due to increased pollution and water depletion. To identify opportunities for increasing the productivity and reducing the environmental impact of cropping systems, it is crucial to assess the associated trade-offs. The paper presents a model-based analysis of how 30 different crop rotations practiced in the North China Plain could be combined at the regional level to overcome trade-offs between indicators of economic, food security, and environmental performance. The model uses evolutionary multi-objective optimization to maximize revenues, livestock products, dietary and vitamin C yield, and to minimize the decline of the groundwater table. The modeling revealed substantial trade-offs between objectives of maximizing productivity and profitability versus minimizing ground water decline, and between production of livestock products and vitamin C yield. Six strategies each defining a specific combination of cropping systems and contributing to different extents to the various objectives were identified. Implementation of these six strategies could be used to find opportunities to mitigate the trade-offs between objectives. It was concluded that a holistic analysis of the potential of a diversity cropping systems at a regional level is needed to find integrative solutions for challenges due to conflicting objectives for food production, economic viability and environmental protection.

Hashita Joyram, Kannan Govindan, Robin Nunkoo

Green building technologies (GBTs) have gained significant momentum as a result of the environmental, energy management and societal problems within the building sector. The insulated block/eco-block is a GBT, which consists of an insulation material that prevents hot/cold air to enter inside buildings, conserve energy and improve indoor comfort in comparison to conventional block. However, conventional building techniques are still dominant in developing countries due to a lack of people's knowledge about GBT, poor interaction with building experts and low support from policymakers. Public acceptance of the eco-block technology is essential for its successful introduction into society. This paper is the first one to systematically review 45 peer-reviewed articles in this field of study with a focus on eco-block. Recent publications have extended theoretical models like (TPB, TAM, DOI, VBN and UTAUT) to study green building consumption. Lack of subjective knowledge about eco-block, lack of trust in the suppliers of eco-block, high price sensitivity, poor education and low-income households are recognised as the major barriers to the technology adoption. The contribution of the paper lies in establishing an original adoption decision framework that groups together a set of (contextual factors, psychological factors and demographic factors) to fill the research gap. The adoption framework could eventually assist the construction experts to analyse the different stages involved in the residents' decision to adopt the eco-block building technology. The paper culminates with a discussion on the application of the conceptual framework as a reference in future GBT usage.

Yasemin Çiftci

The structural, electronic, elastic and optic properties of NaYSi formed in the half-Heusler structure are studied by using ab-initio density-functional theory. The calculated equilibrium lattice constants are compaired with the available experimental and theoretical data. The elastic parameters have calculated. Computed elastic results prove that this compound were mechanically stable. The band gap of this compound predicted to be semiconductor. Further the phonon spectra and optical analysis have been obtained for the energy range of 0–40 eV.

Julianna C. da Silva, Luis F. F. Costa, Daniella P. dos Santos et al.

ABSTRACT This study aimed to carry out an economical and productive analysis of carrot production using different irrigation depths and doses of fertilizer. A randomized block design was used arranged in a 6 × 4 factorial scheme, with three replicates. The treatments were constituted by six irrigation depths: (L1: 210.5, L2: 315.7, L3: 421.0, L4: 526.2, L5: 631.5, and L6: 736.7 mm) and four doses of fertilizer: (F1: 226.9, F2: 340.3, F3: 453.8 and F4: 567.2 kg ha-1) applied via fertigation. At the end of the cycle, four carrot roots were collected per plot to estimate yield. The maximum estimated yield of the carrot was 95.4 t ha-1, obtained using 478.1 mm of water and 538.8 kg ha-1 of fertilizer. The best economic return was achieved with 482.0 mm of water and 460.0 kg ha-1 of fertilizer, giving 95.0 t ha-1. The combination of irrigation and fertilizer allows lesser amount of both to be used, giving greater response than when applied separately.

Minsoo Hong, Yoonsik Choe

The de-blurring of blurred images is one of the most important image processing methods and it can be used for the preprocessing step in many multimedia and computer vision applications. Recently, de-blurring methods have been performed by neural network methods, such as the generative adversarial network (GAN), which is a powerful generative network. Among many different types of GAN, the proposed method is performed using the Wasserstein generative adversarial network with gradient penalty (WGANGP). Since edge information is the most important factor in an image, the style loss function is applied to represent the perceptual information of the edge in order to preserve small edge information and capture its perceptual similarity. As a result, the proposed method improves the similarity between sharp and blurred images by minimizing the Wasserstein distance, and it captures well the perceptual similarity using the style loss function, considering the correlation of features in the convolutional neural network (CNN). To confirm the performance of the proposed method, three experiments are conducted using two datasets: the GOPRO Large and Kohler dataset. The optimal solutions are found by changing the parameter values experimentally. Consequently, the experiments depict that the proposed method achieves 0.98 higher performance in structural similarity (SSIM) and outperforms other de-blurring methods in the case of both datasets.

Belma Zengin Kurt

Bu çalışmada, sinnamaldehitin 9yeni schiff bazı sentezlenmiş ve bu bileşiklerin 2,2-difenil-1-pikrilhidrazil radikal söndürücü kapasitesi(DPPH), Troloks eşdeğeri antioksidankapasitesi (ABTS) ve bakır (II)iyonu indirgeyici antioksidan kapasitesi (CUPRAC) olmak üzere üç farklıyöntemle antioksidan aktivite özellikleri incelenmiştir. Bu bileşiklerin içinde(2,3-dihidroksibenziliden)amino)fenil)-5-fenilpenta-2,4-dien-1-on(4c) bileşiği her üç yönteme göre oldukça etkin bir şekilde antioksidanözellik göstermiştir. Ayrıca sentezlenen bileşiklerin yapı aktivite ilişkisiincelenerek bileşiklerin sahip oldukları grupların antioksidan aktiviteyi hangiyönde etkilediği ortaya konulmuştur.

Sameer S. Gajghate, Vaibhav Khandekar, Shrikrushna Chopade

This study represents experimental data for flow boiling. Experiments were conducted over the horizontal and angular section with inner heating element with the downward flow. Bubble dynamics & heat transfer enhancement in flow boiling using saturated water and betel nut solution has been studied experimentally. The concentration of surfactant was taken 400–1,200 ppm. Bubble behavior is observed for different angle of water tube as a nucleation site. The bubble dynamics was studied using SONY Cyber-shot camera operating at 30 frames per second at atmospheric pressure. The result obtained by aqueous solution with and without additives shows dissimilarity between temperature difference, heat fluxes & heat transfer coefficient. The upstream interface of the bubble is found to exhibit both forward and reverse movement during bubble growth. The little effect of gravity on the bubble growth rate by the heater glass tube inclination. The enhancement is observed due to surface tension of the environment accepted additive solution.

Paweł Gilewski, Maria Grodzka-Łukaszewska, Grzegorz Sinicyn

Numeryczny Model Terenu znajduje coraz częstsze zastosowanie w inżynierii środowiska. Zaprezentowano aplikację pozwalającą na zamianę arkusza NMT w formacie TIN na rastrowy, a następnie połączenie wielu rastrów w jeden (mozaikowanie). Analizie poddano dokładność uzyskiwanych modeli w miejscach nakładania się arkuszy NMT. Łącznie analizie poddano 48 modeli rastrowych uzyskanych 2 metodami interpolacji, o 4 różnych rozdzielczościach i połączonymi za pomocą 6 metod mozaikowania.

Byron Cuesta Quintero, Jorge Andrick Parra Valencia

This article presents a set of elements for cooperation pertinent to free software projects and cooperation theories, based on recognizing how geographically distributed developers in the world find the motivation to create a community around free software and develop successful software. Success cases were also studied worldwide to show how the participants, through computer-mediated communication, resolve individual and group rationality conflicts using scenarios of trust and reciprocity on the use of common resources that allow cooperation for development and maintenance. of free software.

Thalles Evangelista Fernandes de Souza, Emanuel Flávio Campos Costa, Marcos Fábio Porto de Aguiar

É tendência mundial a incorporação de diversas facilidades nas edificações multifamiliares, tais como elevadores, internet predial, sistema de segurança eletrônica, poço profundo, gerador elétrico de emergência, dentre outras. Tais facilidades possuem um custo de manutenção, e este custo é repassado aos condôminos através da taxa condominial. Atualmente, muitos desses moradores de edifícios multifamiliares se queixam dos valores cobrados para a taxa condominial. Em diversos casos, o valor da taxa é superior ao valor do aluguel do imóvel. A proposta do presente trabalho é a de desenvolver uma ferramenta para auxiliar os condôminos, síndicos, compradores e locatários de imóveis residenciais, na previsão do valor da taxa condominial e apontar quais as principais variáveis influenciantes na formação desse valor, tendo como referência o mercado imobiliário de Fortaleza(CE).

B. Olszowski

Celem niniejszej pracy jest uogólnienie wyników otrzymanych w części I. Wyniki te rozszerzono na układy widm częstości własnych pokazane na wykresach widmowych. Przedyskutowano zarówno własności Sturma tych układów, jak i niektóre i numeryczne osobliwości metod wyznaczania częstości własnych. Ustalono ogólne cechy zależności rekurencyjnej między częstościami własnymi i postaciami drgań własnych oraz zilustrowano je odpowiednio dobranymi przykładami. Nacisk położono na zagadnienia wielokrotnych częstości własnych i odpowiadających im form drgań.