Hasil untuk "Engineering"

Ali AbuGneam, Somayeh Nemati, Afshin Babaei

In this research, we propose a new numerical method for solving a class of distributed-order fractional partial differential equations, specifically focusing on distributed-order time fractional wave-diffusion equations. The method begins by introducing a novel generalization of Bernoulli wavelets and deriving an exact result for the Riemann–Liouville integral of these new basis functions. Utilizing the Gauss–Legendre quadrature formula and a strategically chosen set of collocation points, along with approximations for the unknown function and its derivatives, we transform the problem into a system of algebraic equations. An error analysis is then conducted for the approximation of a bivariate function using fractional-order Bernoulli wavelets. Finally, three examples are solved to demonstrate the method’s applicability and accuracy, with the numerical results confirming its effectiveness. These findings demonstrate that the parameters of the basis functions can be adjusted to suit the given problem, thereby enhancing the accuracy of the method.

Seungjae Han, Taeyoung Oh, Soohyeon Lee et al.

With continuous advancements in autonomous driving technology, systematic and reliable safety verification is becoming increasingly important. However, despite the active development of various X-in-the-loop simulation (XILS) platforms to validate autonomous driving systems (ADSs), standardized evaluation frameworks for assessing the credibility of the simulation platforms themselves remain lacking. Therefore, we propose a novel integrated credibility-assessment methodology that combines dynamics-based fidelity assessment, parameter-based reliability assessment, and scenario-based reliability assessment. These three techniques evaluate the similarity and consistency between XILS and real-world test data based on statistical and mathematical comparisons. The three consistency measures are then utilized to derive a dynamics-based correlation metric for fidelity, along with parameter-based and scenario-based correlation and applicability metrics for reliability. The novel contribution of this paper lies in a geometric similarity analysis methodology that significantly enhances the efficiency of credibility assessment. We propose a methodology that enables geometric similarity assessment through spider chart visualization of metrics derived from the credibility-assessment process and shape comparison, based on Procrustes, Fréchet, and Hausdorff distances. As a result, speed is not a dominant factor for credibility evaluation, enabling assessment with a single representative speed test; the framework simplifies the XILS evaluation and enhances ADS validation efficiency.

Susheel Kumar Nethi, Venugopal Gunda, Nagabhishek Sirpu Natesh et al.

Summary: Pancreatic cancer (PC) exhibits profound metabolic adaptations that support tumor progression, survival, and therapy resistance. Hypoxia-inducible factor-1α (HIF-1α) is a key regulator of these processes, promoting metabolic reprogramming and chemoresistance. Given that mitochondrial metabolites modulate HIF-1α stability, targeting mitochondrial metabolism offers a promising therapeutic strategy. Niclosamide (Nic), a clinically approved anthelmintic, disrupts mitochondrial function but is limited by poor bioavailability. To overcome this, we developed polyanhydride-based Nic nanoparticles (NicNps) to enhance bioavailability and efficacy. NicNps impaired mitochondrial function, suppressed metabolism, downregulated HIF-1α, and inhibited growth of PC cells and orthotopic gemcitabine (Gem)-resistant mouse tumor models. Notably, NicNps combined with Gem overcame therapy resistance by synergistically reducing tumor hypoxia and HIF-1α-driven metabolic reprogramming. These findings highlight NicNps as a mitochondria-targeted, nanoparticle-based therapy that enhances Nic’s bioavailability while suppressing HIF-1α-driven adaptations. NicNps in combination with Gem offer a promising strategy to overcome therapy resistance and improve treatment outcomes in patients with pancreatic cancer.

Ifiok Udoidiok, Fuhao Li, Jielun Zhang

Machine learning (ML) has become a cornerstone of critical applications, but its vulnerability to data poisoning attacks threatens system reliability and trustworthiness. Prior studies have begun to investigate the impact of data poisoning and proposed various defense or evaluation methods; however, most efforts remain limited to quantifying performance degradation, with little systematic comparison of internal behaviors across model architectures under attack and insufficient attention to interpretability for revealing model vulnerabilities. To tackle this issue, we build a reproducible evaluation pipeline and emphasize the importance of integrating robustness with interpretability in the design of secure and trustworthy ML systems. To be specific, we propose a unified poisoning evaluation framework that systematically compares traditional ML models, deep neural networks, and large language models under three representative attack strategies including label flipping, random corruption, and adversarial insertion, at escalating severity levels of 30%, 50%, and 75%, and integrate LIME-based explanations to trace the evolution of model reasoning. Experimental results demonstrate that traditional models collapse rapidly under label noise, whereas Bayesian LSTM hybrids and large language models maintain stronger resilience. Further interpretability analysis uncovers attribution failure patterns, such as over-reliance on neutral tokens or misinterpretation of adversarial cues, providing insights beyond accuracy metrics.

Jiale Liu, Xinlei Cai, Zijie Meng et al.

Abstract Potential evaluation to assist demand response decisions has garnered significant attention with the development of new power systems. However, existing data‐driven methods are challenging to properly exploit multivariate features and the process of response potential evaluation is unclear. Therefore, the authors propose an evaluation method that fuses expert features with multi‐image inputs and analyses the model evaluation process based on gradient. First, typical load profiles are extracted by the proposed procedure. Next, features derived from expert knowledge are calculated from the perspectives of adjustability, regularity, and sensitivity of electricity usage. Additionally, the typical load profile's recurrence plot, Markov leapfrog field, and Gramian angle field are created and incorporated into the colourful image as inputs. Then, the evaluation results are obtained by a two‐stream neural network fusing multivariate features. In the experiments, the proposed method is validated and discussed by comparing with many existing methods using London household users' data under the time‐of‐use price, providing new insights for demand response potential evaluation.

Xinhui Zheng, Qiyan Tian, Qifeng Zhang

Recently, as humans have become increasingly interested in ocean resources, underwater vehicle-manipulator systems (UVMSs) have played an increasingly important role in ocean exploitation. To realize precise operation in underwater narrow spaces, the fly arm underwater vehicle manipulator system (FAUVMS) is proposed with manipulators as its core. However, this system suffers severe dynamic coupling effects due to the combination of small vehicle and big manipulators. To resolve this issue, we propose a robust adaptive controller that contains two parts. In the first part, the extended Kalman filter (EKF) is designed to estimate the system states and predicts external disturbances to achieve adaptive control. In the second part, a chattering-free sliding mode control (SMC) is designed to converge the tracking errors to zero, thus guaranteeing the robustness of the controller. We constructed the simulation platform based on the geometric model of FAUVMS, and various simulations are carried out under different situations. Compared to the traditional methods, the proposed method has a faster convergent speed, a better robustness and adaptiveness to external disturbances, and the tracking errors of positions of the vehicle and each end-effector are much smaller.

T. Testasecca, P. Catrini, M. Beccali et al.

District Heating Network is identified as a promising technology for decarbonizing urban areas. Thanks to the surplus of heat available from distributed renewable energy plants, a typical heat consumer of the network could become an energy producer during the day (typically referred to as a “prosumer”). Most of the models for thermal grids developed during past years usually assumed a centralized production of the consumed heat. The increasing presence of prosumers will require accurate dynamic modelling to monitor the changes induced in the thermohydraulic parameters of the network. To fill this knowledge gap, this paper aims at developing a model of a thermal grid with prosumers in the TRNSYS environment. The model allows for the dynamic monitoring of the main thermohydraulic parameters of the network. To show these capabilities, a ring-shaped network serving a cluster of 10 residential users located in Palermo (Italy) was assumed as the case study. Different scenarios are investigated based on the presence of solar collectors, prosumers along the network, and cooling by an absorption chiller. The achievable energy and emissions savings are calculated. The results of the study show that even only decreasing the operating temperature can significantly reduce heat losses via the network pipes. In particular, a temperature drop from 100 °C to 80 °C can reduce heat losses by 27.1%. Furthermore, the heat losses can be decreased by up to 52.8% when the network temperature is lowered from 100 °C to 60 °C. Additionally, the presence of prosumers and the solar field could lead to a 31.3% reduction in the energy produced by the centralized plant and a 17.6% reduction in energy consumed for pumping.

Anqi Gao, Bing Sun, Mengyuan Yan et al.

The study focuses on addressing the image defocusing issue caused by motion errors in highly squinted Synthetic Aperture Radar (SAR). The traditional auto-focusing algorithm, Phase Gradient Autofocus (PGA), is not effective in this mode due to difficulties in estimating the phase gradient accurately from strong point targets. Two main reasons contribute to this problem. Firstly, the direction of the energy-distributed lines in the Point Spread Function (PSF) does not align with the image’s azimuth direction in highly squinted mode. Secondly, the wavenumber spectrum of high squint SAR images obtained using the Back-Projection Algorithm (BPA) varies spatially, causing aliasing in the azimuth spectrum of all targets. In this paper, a new auto-focusing method is proposed for highly squinted SAR imaging. The modifications to the BP imaging grids have been implemented to address the first problem, while a novel wavenumber spectrum shifting and truncation method is proposed to accurately extract the phase gradient and tackle the spatial variation issue. The feasibility of the proposed algorithm is verified through simulations with point targets and processing of real data. The evaluation of the image shows an average improvement of four times in PSLR (Peak-Sidelobe-to-Noise Ratio).

Yen-Ting Chang, Ming-Hao Lee, Ming-Wen Chu et al.

The microstructures and phase formations of Ti20Zr15Hf15Ni35Cu15 high entropy shape memory alloy (HESMA) under different aging conditions were investigated in this study. At aging temperatures below 500 °C, a large amount of the H-phase formed, and the martensitic transformation temperatures were suppressed due to the strain field around the H-phase. Aging treatment at 600 °C caused a eutectoid reaction, which yielded a lamellar structure composed of (Zr,Hf)7Cu10 and Ti2Cu phases. When the aging treatment was increased to 700 °C, the lamellar structure was no longer observed, but (Zr,Hf)7Cu10 and newly-formed Ti2Ni phases formed around the original Ti2Ni phase. Experimental results demonstrated that the H-phase precipitation, eutectoid decomposition, and (Zr,Hf)7Cu10 formation occurred at different aging temperatures. These results could be utilized to adjust the martensitic transformation temperatures and design microstructures, providing a new strategy for developing TiZrHfNiCu HESMAs.

Jiankui Liu, Jiankui Liu, Jiankui Liu et al.

The porcine reproductive and respiratory syndrome virus (PRRSV) is one of the most important pathogens causing substantial economic losses to the Chinese swine industry. In this study, we analyzed the complete genome sequences of four PRRSV isolates (PRRSV2/CN/SS0/2020, PRRSV2/CN/SS1/2021, PRRSV2/CN/L3/2021, and PRRSV2/CN/L4/2020) isolated from a single pig farm from 2020 to 2021. The genomes of the four isolates were 14,962–15,023 nt long, excluding the poly (A) tails. Comparative analysis of the genome sequences showed that the four isolates shared 93.2–98.1% homology and they had no close PRRSV relatives registered in the GenBank (<92%). Furthermore, PRRSV2/CN/SS0/2020 and PRRSV2/CN/SS1/2021 had characteristic 150-aa deletions (aa481+aa537-566 +aa628–747) that were identical to the live attenuated virus vaccine strain TJM-F92 (derived from the HP-PRRSV TJ). Further analysis of the full-length sequences suggests that the four isolates were natural recombinant strains between lineages 1 (NADC30-like), 3 (QYYZ-like), and 8.7 (JXA1-like). Animal experiments revealed discrepancies in virulence between PRRSV2/CN/SS0/2020 and PRRSV2/CN/L3/2021. The strain with high homology to HP-PRRSV demonstrates higher pathogenicity for pigs than the other isolate with low homology to HP-PRRSV. Taken together, our findings suggest that PRRSVs have undergone genome evolution by recombination among field strains/MLV-like strains of different lineages.

Jiuxin Wang, Yutian Luo, Zhengming Yang et al.

In order to improve the measurement speed and prediction accuracy of unconventional reservoir parameters, the deep neural network (DNN) is used to predict movable fluid percentage of unconventional reservoirs. The Adam optimizer is used in the DNN model to ensure the stability and accuracy of the model in the gradient descent process, and the prediction effect is compared with the back propagation neural network (BPNN), K-nearest neighbor (KNN), and support vector regression model (SVR). During network training, L₂ regularization is used to avoid over-fitting and improve the generalization ability of the model. Taking nuclear magnetic resonance (NMR) T₂ spectrum data of laboratory unconventional core as input features, the influence of model hyperparameters on the prediction accuracy of reservoir movable fluids is also experimentally analyzed. Experimental results show that, compared with BPNN, KNN, and SVR, the deep neural network model has a better prediction effect on movable fluid percentage of unconventional reservoirs; when the model depth is five layers, the prediction accuracy of movable fluid percentage reaches the highest value, the predicted value of the DNN model is in high agreement with the laboratory measured value. Therefore, the movable fluid percentage prediction model of unconventional oil reservoirs based on the deep neural network model can provide certain guidance for the intelligent development of the laboratory’s reservoir parameter measurement.

Fateme Hassanli, Mohammad Hossein Paydar

In the present work, effect of structural design on the mechanical properties of aluminum foams was studied. Aluminum foams with a relative density in the range of 0.28–0.48 with uniform and graded pore frequency were fabricated through powder metallurgy route by using carbamides as space holder, where double action die pressing process was used for producing green compacts. Carbamide space holders were removed by leaching in water plus heating processes, whereafter the samples were sintered at 640 °C for 2 h in air. Mechanical properties and energy absorption capability of the fabricated foam samples were evaluated by the means of compression test. The results showed that correct modification in pore distribution can significantly improve mechanical properties of the fabricated foam by compensating the undesirable density gradient created in the foam structure due to the die wall friction. So that for the foams with a relative density of 0.28, introducing desired gradation in pore frequency caused nearly 100% increase in plateau stress and more than 75% improvement in energy absorption ability of the fabricated foam.

Zhao Z.-Y., Zhao J.-X., Cui Y. et al.

The physicochemical properties of slag are of great importance in pyrometallurgy. If there is a volatile component in the slag, evaporation will inevitably occur. As a result, the slag composition will change, and the measured results will be inconsistent with the original slag composition. Therefore, the traditional methods can be applied to determine the properties of slag, however, the change in slag composition will lead to the inaccuracy of the results. Two typical kinds of slag ESR slag with higher CaF2 and Pb smelting reduction slag with higher PbO were chosen, and melting point measurements were taken as an example to demonstrate the new method in practice. Weight loss measurements and evaporation test with thermogravimetric (TG) analysis, as well as high-temperature mass spectrometer (MS) tests were carried out to identify the volatiles. It was found that CaF2 and MgF2 is the main volatiles with a small amount of AlF3 to ESR slag and PbO is the main volatile with a small amount of ZnO. Based on these points and the weight loss, the slag melting points measured with traditional method and the slag chemical composition were modified to fit the melting point value. This way is proved to be feasible in theory and practice. Some suggestion for further research are proposed. The work will be of significance for both slag and molten salt with volatiles.

Zhouzheng Gao, You Li, Yuan Zhuang et al.

Reliable and continuous navigation solutions are essential for high-accuracy location-based services. Currently, the real-time kinematic (RTK) based Global Positioning System (GPS) is widely utilized to satisfy such requirements. However, RTK’s accuracy and continuity are limited by the insufficient number of the visible satellites and the increasing length of base-lines between reference-stations and rovers. Recently, benefiting from the development of precise point positioning (PPP) and BeiDou satellite navigation systems (BDS), the issues existing in GPS RTK can be mitigated by using GPS and BDS together. However, the visible satellite number of GPS + BDS may decrease in dynamic environments. Therefore, the inertial navigation system (INS) is adopted to bridge GPS + BDS PPP solutions during signal outage periods. Meanwhile, because the quality of BDS geosynchronous Earth orbit (GEO) satellites is much lower than that of inclined geo-synchronous orbit (IGSO) satellites, the predicted observation residual based robust extended Kalman filter (R-EKF) is adopted to adjust the weight of GEO and IGSO data. In this paper, the mathematical model of the R-EKF aided GEO/IGSO/GPS PPP/INS tight integration, which uses the raw observations of GPS + BDS, is presented. Then, the influences of GEO, IGSO, INS, and R-EKF on PPP are evaluated by processing land-borne vehicle data. Results indicate that (1) both GEO and IGSO can provide accuracy improvement on GPS PPP; however, the contribution of IGSO is much more visible than that of GEO; (2) PPP’s accuracy and stability can be further improved by using INS; (3) the R-EKF is helpful to adjust the weight of GEO and IGSO in the GEO/IGSO/GPS PPP/INS tight integration and provide significantly higher positioning accuracy.

Hsien-Chin Chiu, Chia-Hao Liu, Yi-Sheng Chang et al.

The surface morphology optimization of ohmic contacts and the Mg out-diffusion suppression of normally off p-GaN gate high-electron-mobility transistors (HEMTs) continue to be challenges in the power electronics industry in terms of the high-frequency switching efficiency. In this study, better current density and reliable dynamic behaviors of p-GaN gate HEMTs were obtained simultaneously by adopting low-temperature microwave annealing (MWA) for the first time. Moreover, HEMTs fabricated using MWA have a higher ION/IOF ratio and lower gate leakage current than the HEMTs fabricated using rapid thermal annealing. Due to the local heating effect, a direct path for electron flow can be formed between the two-dimensional electron gas and the ohmic metals with low bulges surface. Moreover, the Mg out-diffusion of p-GaN gate layer was also suppressed to maintain good current density and low interface traps.

Tomoya Suzuki, Takeshi Ogata, Mikiya Tanaka et al.

The refining of platinum group metals is based mainly on solvent extraction methods, whereas Ru is selectively recovered by distillation as RuO4. Replacement of distillation by extraction is expected to simplify the purification process. To develop an effective extraction system for Ru, we analyzed the Ru species in HCl with ultraviolet-visible (UV-Vis) and Ru K-edge extended X-ray absorption fine structure (EXAFS) spectroscopies, and we examined the properties of Ru extracted with N-2-ethylhexyl-bis(N-di-2-ethylhexyl-ethylamide) amine (EHBAA) and trioctylamine (TOA). EXAFS and UV-Vis spectra of Ru in HCl solutions revealed that the predominant Ru species in 0.5–10 M HCl solutions changed from [RuCl4(H2O)2]− to [RuCl6]3− with the HCl concentration. The extraction percentages (E%) of Ru in the EHBAA system increased with increasing HCl concentration, reached 80% at [HCl] = 5 M, and decreased at higher HCl concentrations; the corresponding E% for TOA were low. EXAFS analysis of the extracted complex indicated that the Ru3+ had 5 Cl− and 1 H2O in its inner coordination sphere. The similarity of the dependence on HCl concentrations of the E% in the EHBAA system and the distribution profile of [RuCl5(H2O)]2− on [RuCln(H2O)6−n]3−n suggested that the EHBAA extracted the pentachlorido species.

W. Bodaszewski

SUMMARY OF THE WHOLE PAPER: By now, the SADSF method is practically the only tool of shape design of complex machine elements that provides an effective solution even to the problems of 3D distribution of the material, and at the same time it is still enough user friendly to be useful for engineers. This unique property of the method is due to the existence of its simple, application version. When using it, a design engineer does not need to solve by oneself any statically admissible field – which could be very difficult – but obtains such a solution by assembling various ready-made particular solutions. The latter are in general obtained by means of individual and complex analyses and provided to a designer in a form of libraries. The algorithms presented in this paper break up with the individual approach to a particular field. The algorithms are the first ones of general character, as they apply to the fundamental problems of the method. The algorithms aid solving practically any boundary problem that one encounters in the tasks of construction of 2D statically admissible, discontinuous stress fields, first of all the limit fields. In the presented approach, one deals first with the fields arising around isolated nodes of stress discontinuity lines (Parts II and III), then integrates these fields into 2D complex fields (Part IV). The software, created on the basis of the algorithms, among other things, allows one to quickly find all the existing solutions of the discontinuity line systems and present them in a graphical form. It gives the possibility of analysing, updating and correcting these systems. In this way, it overcomes the greatest difficulty of the SADSF method following from the fact that the systems of discontinuity lines are not known a priori, and appropriate relationships are not known either, so that they could only be found in an arduous way by postulating the line systems, and verifying them. Application version of the SADSF method is not described in this paper; however, a reference is given to inform the reader where it can be found.

Eyad K. Say hood, Nisreen S. Mohammed, Ibtihal Fadhil Ali

In this research paper, a 3-D finite element model was used for the analysis of curved concrete slab on steel girder bridges. A parametric study was carried out to calculate the load distribution factors for horizontally curved steel I-girder bridges based on (AASHTO LRFD) live loads .The bridges are analyzed by three dimensional finite elements using SAP 2000 software (Structural Analysis Program) with shell elements. The parameters considered in this study were: span-to-radius of curvature ratio, span length and the analysis of bridge will be performed for the case of full live load and partial live loads. The full data are given together with AASHTO LRFD calculations up to L/R equal to (0.6).

N. J. Cowan, D. Famulari, P. E. Levy et al.

Uptake (or negative flux) of nitrous oxide (N₂O) in agricultural soils is a controversial issue which has proved difficult to investigate in the past due to constraints such as instrumental precision and methodological uncertainties. Using a recently developed high-precision quantum cascade laser gas analyser combined with a closed dynamic chamber, a well-defined detection limit of 4 μg N₂O-N m⁻² h⁻¹ could be achieved for individual soil flux measurements. 1220 measurements of N₂O flux were made from a variety of UK soils using this method, of which 115 indicated uptake by the soil (i.e. a negative flux in the micrometeorological sign convention). Only four of these apparently negative fluxes were greater than the detection limit of the method, which suggests that the vast majority of reported negative fluxes from such measurements are actually due to instrument noise. As such, we suggest that the bulk of negative N₂O fluxes reported for agricultural fields are most likely due to limits in detection of a particular flux measurement methodology and not a result of microbiological activity consuming atmospheric N₂O.