Search Results (1,414)

This study investigates the thermo-mechanical response of geocell-reinforced concrete pavements through scaled model tests and three-dimensional finite element analyses. Static, thermal, traffic, and coupled temperature–loading tests were conducted to clarify the deformation evolution, strain distribution, and damage-related response of the reinforced structure. The results show that, under static loading, pavement settlement evolves through three stages, namely initial compaction, plastic development, and stable strengthening, indicating progressive mobilization of geocell confinement. Under thermal loading, slab strain exhibits pronounced spatial and temporal non-uniformity, and the slab center is identified as the thermally sensitive zone. Under coupled temperature–loading conditions, both strain and settlement show a non-monotonic response near 1.1–1.3 kN, suggesting a potential damage-initiation range. Post-test crack observations further provide direct qualitative evidence that local cracking damage occurred in the slab under representative loading conditions. Under traffic loading, permanent deformation accumulates with load repetitions and is highly sensitive to load amplitude, indicating a load-sensitive transition in cumulative deformation behavior rather than a definitive fatigue threshold. Numerical results further show that geocell reinforcement reduces central settlement by 17.4% relative to plain concrete pavement and by 7.6% relative to doweled pavement, while producing a smoother deflection basin and a more uniform stress distribution. Parametric analyses indicate that the optimum geocell height is approximately one-third of the slab thickness; beyond this range, the marginal reinforcement benefit decreases. Overall, the results demonstrate that geocell reinforcement can effectively improve load transfer, deformation compatibility, and thermo-mechanical stability of concrete pavements under the investigated conditions. Full article

In a bid to investigate the optimum transportation method for offshore wind-produced hydrogen (H₂) and assess the feasibility of repurposing the existing oil and gas infrastructure for H₂ transmission, this paper assesses the existing H₂ transportation methods with a comprehensive review of the H₂ impact on the existing natural gas pipeline infrastructure. To establish the possibility of repurposing the existing natural gas (NG) pipelines for H₂ gas transport, this paper reviews the influential technical measures—composition, pressure, temperature, volumetric energy density, density, and pressure drop—to assess whether the characteristics of hydrogen gas are compatible with the natural gas pipeline infrastructure. Based on these reviews, it was found that the current NG pipeline pressure exacerbates the H₂ embrittlement; for the existing NG pipelines to be repurposed, the operating pressure should be reduced, and the pipeline material should be revised. It was found that higher strength steels can be re-used with major modifications, or the pipeline should be constructed from material grade X52 or below. Nevertheless, the fitness of the existing NG pipelines for H₂ transmission should be assessed on a case-by-case basis and other factors such as erosion, leakage, pressure cycling, monitoring (e.g., distributed fiber-optic sensing technology) and a rigorous assessment of welds and joints should also be considered. Full article

Against the backdrop of dual-carbon goals and resource constraints, the high-value utilization of recycled fine aggregates (RFAs) remains limited, leading to inconsistent engineering performance and insufficient durability. Enzyme-induced carbonate precipitation (EICP) represents a promising low-carbon cementation method, yet its deposition uniformity and cementation efficiency are influenced by the pore structure of granular media and associated mass transfer pathways. This study employs a two-stage experimental design to investigate the synergistic effects of particle size distribution characteristics, represented primarily by d₅₀, and fiber addition on EICP-cemented RFA. Phase I (fiber-free; d₅₀ = 0.67–1.14 mm) results indicate that, across the tested gradation schemes, the CaCO₃ content generally decreased from 9.49% to 7.72% as the representative d₅₀ increased, while the dry density changed only slightly (1.637–1.617 g/cm³). However, the unconfined compressive strength (UCS) decreased from 1000 kPa to 541 kPa (45.9% reduction), indicating that strength is primarily governed by the connectivity of the cementation network rather than solely by the degree of densification. In Phase II, glass fiber (GF), polypropylene fiber (PPF), and jute fiber (JF) were incorporated into the ERFA4 gradation scheme selected for fiber modification. All three systems exhibited a unimodal optimum pattern: the peak CaCO₃ contents reached 10.71% (GF 0.5%), 10.11% (PPF 0.7%), and 11.46% (JF 0.7%), corresponding to peak UCS values of 1917, 1874, and 2450 kPa, respectively. Microscopic analysis suggested that fiber bridging coupled with CaCO₃ deposition may contribute to the formation of a “fiber-CaCO₃-particle” stress-transfer network, which is consistent with the observed enhancements in load-bearing capacity, ductility, and post-peak stability. Full article

The current study proposes an improved DenseNet-based Sequential Multimodal Biometric Authentication System, involving face and ear modality for better human identification. The architecture is composed of three convolutional layers and two dense layers, which are optimized for obtaining the discriminative spatial representations in 200 × 200 pixel facial and ear images. Evaluation is performed based on strict 5-fold subject disjoint cross-validation data to ensure the unbiased assessment. The model proposed attained a steady classification accuracy of 97.1 ± 0.79%, and balanced values for Precision, Recall and F1-score under controlled validation conditions, while the Performance analysis including False Acceptance (FAR), False Rejection (FRR) and Equal Error Rate (EER) showed that the EER found is around 1.05% at the optimum operating value. Comparative experiments between parallel feature concatenation and sequential verification techniques show that the sequential framework yields decreased FAR, when compared to the parallel framework, without having a detrimental effect on overall accuracy, while the Statistical validation by analysis of variance shows that the incremental architectural improvements have a significant impact on performance improvements. Findings of this analysis show a “score distribution” that both “single-trait and traditional multifactor systems” exceed the presentation of a novel method for Nex-G authentication solutions. This study advances biometric security by demonstrating how multimodal fusion may address the increasing global demand for robust and privacy-aware authentication methods, thereby setting a standard for intelligent multimodal recognition systems. Full article

This paper introduces a hybrid metaheuristic approach for the reconfiguration of electric distribution networks, integrating Simulated Annealing (SA) and Tabu Search (TS) to accelerate convergence and enhance exploration of the solution space. The method employs a selective mesh-based neighbor generation strategy, which substantially reduces the search space while maintaining operational feasibility (radial topology, voltage, and current limits). The approach was implemented in Python and integrated with DIgSILENT PowerFactory, enabling the direct evaluation of losses, voltages, and currents for reproducible and scalable analysis. Validation on 5-, 16- and 33-bus benchmark systems consistently reached the global optimum across 100 simulation runs, demonstrating robustness and computational efficiency. A real-world application was performed on the 10 kV primary distribution network of Huancayo, Peru, where the proposed method achieved a 10.4% reduction in active losses, improved the minimum voltage from 0.931 to 0.949 p.u., and partially relieved feeder overloads. These results confirm the method’s suitability for both academic benchmarking and practical deployment in Latin American distribution systems. Full article

This paper introduces D³O-GT, a distributed optimization framework designed to operate under partial, heterogeneous, and delayed information—conditions commonly encountered in large-scale logistics and networked decision support systems. The proposed approach integrates gradient tracking with delay-aware updates to address the steady-state bias and instability that often affect classical distributed gradient methods. We formulate a consensus optimization model that captures decentralized decision variables while preserving global optimality, and we develop an algorithmic structure that balances convergence accuracy, communication efficiency, and robustness to asynchronous updates. Extensive numerical experiments demonstrate that D³O-GT achieves machine precision convergence in synchronous settings and remains stable under bounded communication delays, converging to a small neighborhood of the optimum. In contrast, conventional distributed gradient descent exhibits significant residual error under the same conditions. Scalability analyses further indicate that the proposed method maintains favorable iteration complexity as the number of agents increases. These results position D³O-GT as a practical and scalable solution for distributed decision-making environments, with direct relevance to logistics-oriented applications such as resource allocation, coordination of networked services, and real-time operational planning. Full article

Reactive power compensation devices (RPCDs) are crucial for improving the efficiency of energy systems. Distribution systems are commonly modeled under the simplifying assumption of balanced operation, which does not accurately represent real operating conditions. Motivated by the need to develop an effective computational tool for the proper selection of RPCDs, this paper proposes the application of the experience exchange strategy (EES) to the coordinated design of RPCDs. To the best of the authors’ knowledge, this is the first study to employ EES for this purpose. The proposed methodology is validated through two case studies. In the first case, an extensive exploration of the search space is performed by repeating the optimization process, resulting in a solution with a high probability of being the global optimum. Under this scenario, a comparative analysis shows that EES outperforms the genetic algorithm by 7.4%. In the second case, EES is compared with other popular heuristic techniques, including particle swarm optimization (PSO), without performing a deep exploration of the search space, observing that EES ranks in the middle, with a difference of 11.9% relative to PSO. Overall, the results confirm that the proposed EES-based framework constitutes a reliable and efficient approach. Full article

The present study deals with the problem of irregular temperature distribution, simultaneous under-firing and over-firing, and their resultant efficiency and quality problems in a mechanical lime vertical kiln powered by domestic waste flue gas. The numerical simulation and structure optimization were carried out based on a 150 kg/h pilot-scale kiln. This combined model was built on the ANSYS Fluent 2022 R1 platform with UDF and UDS, incorporating limestone decomposition kinetics to enable the solution of gas and solid energy equations separately, and simulation of complex transfer and reaction processes. To correct the separation of flows at one inlet, a symmetric four-direction (00, 900, 1800, 2700) air intake plan was suggested. The findings show that this design essentially transforms the internal flow field into uniform and symmetrical temperature and concentration distributions. The calcination region contained both gas and solid temperatures in the optimum range to produce active lime. Specifically, the optimized kiln achieved a temperature range of 1190–1450 K in the calcination zone, a decomposition rate of approximately 82.7% (compared to 5.3% in the original model), and an increase in effective CaO content from 81.7% to 87.7%, with validation errors below 15%. It was demonstrated that the model is reliable, since the outlet simulated values correlated well with the measured ones. The preheating, calcining, and cooling zones’ heights of the optimized kiln adhered to the design requirements. This research is innovative in its application of a multi-physics coupling model with a varying heat source in a kiln and, in turn, identifies the synergism improvement process in the flow, temperature, concentration, and reaction fields. Full article

In this paper, an innovative design of a silicon spiral drift detector (SDD) has been proposed. In this design, gaps under the SiO₂ layer between the cathode rings are kept constant, with a minimum value to reduce the surface leakage current. The cathode pitch profile $\mathrm{P}\left(\mathrm{r}\right)$ as a function of radius $\mathrm{r}$ is allowed to change in an arbitrary way to achieve the optimum field distribution. The concept, design considerations, modeling and electrical simulations have been carried out for this novel structure with a hexagonal spiral silicon drift detector. Using one-dimensional analyses, we obtain the exact solution of the spiral design $\mathrm{r}=\mathrm{r}\left(\mathrm{\theta }\right)$ with a near-arbitrary pitch profile $\mathrm{P}\left(\mathrm{r}\right)={\mathrm{P}}_1{\left({\displaystyle \frac{\mathrm{r}}{{\mathrm{r}}_1}}\right)}^{{\displaystyle \frac{1}{\mathrm{\eta }}}}$, with $\mathrm{\eta }$ as an arbitrary real number. We also obtained the electric potential and field profiles on both surfaces of the detector. Using a Technology Computer-Aided Design (TCAD) tool, we made 3D simulations of the detector’s electrical properties. The hexagonal spiral silicon drift detector has excellent electrical properties: a uniform electric field, smooth distribution of electric potential and electron concentration, and a clear electron drift channel. The distributions of the electric field, electric potential, and electron concentration are symmetrical and smooth, which is beneficial for applications in photon sciences (X-ray) and safeguards and homeland security (particle radiation). The theoretical work and simulation results serve as solid foundations for the detector design and the expansion of semiconductor technology. Full article

Halophilic proteases are valuable in industrial applications due to their resistance to harsh conditions. HtrA2 serine protease is widely distributed and conserved among eukaryotes and prokaryotes. However, HtrA2 proteases from archaea have been poorly characterized. In this study, htrA2 from haloarcheon Haloarcula sp. TG1 was cloned and corresponding nucleotide and amino acid sequences were analyzed. Recombinant HtrA2 was produced in Escherichia coli, and biochemical properties of purified HtrA2 were characterized. HtrA2 was immobilized for the first time using polyhydroxybutyrate (PHB) nanoparticles. Additionally, potential of HtrA2 as a detergent additive was evaluated by its bloodstain removal activity. Recombinant HtrA2 showed its optimum activity at 50 °C, pH 7.0, and 3.0 M NaCl. HtrA2 activity was highly retained over wide temperature (40 to 60 °C) and pH ranges (pH 5.0 to 11.0). Moreover, various organic solvents, inhibitors and metal ions were well tolerated by the enzyme. Acetone and Fe²⁺ significantly increased HtrA2 activity, while it was not inhibited by phenylmethylsulfonyl fluoride and sodium dodecyl sulfate. Also, immobilization of HtrA2 onto PHB nanoparticles improved its reusability. Furthermore, HtrA2 successfully removed the bloodstain from cotton fabric. This comprehensive characterization of HtrA2 demonstrates that recombinant HtrA2 obtained from Haloarcula sp. TG1 is promising for industrial applications. Full article

Multi-regional electricity markets increasingly struggle to balance data privacy requirements with the computational burden of centralized clearing. To address this issue, this study proposes a distributed joint-clearing framework based on the Alternating Direction Method of Multipliers (ADMM) to co-optimize pumped storage hydropower (PSH) and battery energy storage systems (BESS) across energy, frequency regulation, and reserve markets. A mixed-integer programming model is formulated to maximize social welfare, explicitly capturing the time-coupled, energy-oriented characteristics of PSH and the fast-response, power-oriented capabilities of BESS. The global problem is decomposed into regional subproblems that can be solved in parallel. An adaptive penalty parameter strategy is further introduced to dynamically balance primal and dual residuals, thereby improving convergence and robustness in the mixed-integer setting. To address the limited economic interpretability of dual variables in mixed-integer programming (MIP) models, an approximate marginal pricing mechanism based on subproblem sensitivity analysis is proposed. A two-region, 24 h case study shows that the proposed method converges in around 65 iterations and achieves a social welfare outcome within 0.61% of the centralized optimum. By minimizing information exchange, the framework offers a scalable and privacy-aware solution for future multi-regional market operations involving heterogeneous energy storage resources. Full article

In this study, phenolic hydroxyl-functionalized poly(α,β-[N-(2-hydroxyethyl)-D, L-aspartamide]) (PHEA-HP) was used to prepare hydrogel beads via an emulsion-enzymatic gelation process. The effects of the preparation conditions on the size and size distribution span of the hydrogel beads were investigated. Initially, single-factor experiments were conducted to determine the range of preparation conditions for hydrogel beads. Subsequently, a Box–Behnken design combined with response surface methodology (BBD–RSM) was employed to optimize the emulsification parameters for preparing hydrogel beads, with three numerical independent variables (oil-to-water ratio, homogenization rate, and Span 80 dosage) and two responses (size and size distribution span). The results indicated that the size distribution span fit the quadratic model well and was more sensitive to the three independent variables than size. The optimal preparation conditions were validated to be an oil-to-water ratio of 10.3, a homogenization rate of 2930 rpm, and a Span 80 dosage of 2.0%. At the optimum point, the prepared PHEA-HP hydrogel beads were spherical, with an average size of 14.0 ± 0.2 μm and a size distribution span of 0.185 ± 0.010. Full article

This study investigates the feasibility of using calcined pumice as a sustainable precursor for geopolymer production. Natural pumice was calcined at different temperatures (600, 750, and 900 °C) and durations (1, 2, and 4 h). The effects of calcination were evaluated through color change, particle size distribution, scanning electron microscopy, energy-dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, and X-ray diffraction. The results showed that calcination induced structural and mineralogical modifications in pumice, including increased disorder in the aluminosilicate network and partial recrystallization, which enhanced its reactivity. Consequently, geopolymer mortars produced with calcined pumice exhibited significantly improved compressive strength, with the highest strength of 53.5 MPa obtained for the sample calcined at 750 °C for 1 h, corresponding to an 84.5% increase compared to the mortar produced with raw pumice. In addition, calcination at 600 °C and 900 °C significantly improved water resistance. Considering mechanical performance, durability-related properties, and energy efficiency together, the calcination condition of 600 °C for 2 h was identified as the optimum treatment. These findings demonstrate that calcined pumice is a promising and sustainable precursor for geopolymer production. Full article

Mineral processing may decisively influence recycled aggregate (RA) production, yet it is systematically underreported. This critical review screened 338 Scopus-indexed publications (2004–2024) and retained 204 studies after eligibility assessment. Reporting on comminution was limited: ~52% (105 studies) of studies did not explicitly mention crushing, while ~26% (53 studies) identified the crusher type, and only about 1% (two articles) reported operating conditions, which undermines reproducibility and cross-study comparability. RA quality is application-/market-dependent. The literature was classified into cement-based materials (46.1%), pavement applications (44.6%), and fundamental studies without application (9.3%). For cement-based materials, water absorption and compressive strength were the most frequently reported primary and secondary properties, respectively. For pavement applications, particle-size distribution and optimum moisture content predominated. Overall, mineral processing directly governs the primary attributes of recycled aggregates (RAs) and indirectly influences their secondary performance outcomes. The main gap identified in the literature is the lack of clear recommendations for processing procedures, which limits the reproducibility and comparability of reported results. To address this limitation, this article proposes a mineral-processing framework intended to standardize both RA processing and reporting practices, thereby improving crosslink study comparability, experimental reproducibility, and evidence-based specification according to end-use requirements. Full article

This study presents a three-dimensional transient Computational Fluid Dynamics (CFD) analysis of a Venturi injector system used in a textile machine for removing excess water from fabrics after dyeing or washing processes. The main objective is to determine the optimum operating conditions by investigating the coupled effects of nozzle diameter and inlet pressure on pressure distribution, velocity field, and suction performance. Numerical simulations were performed for three nozzle diameters (d_n = 14 mm, 15 mm, and 16 mm) and three inlet pressure values (P_i = 10 bar, 12 bar, and 15 bar). The results show that the Venturi injector performance is highly sensitive to the interaction between geometric and operating parameters. Increasing the inlet pressure from 10 bar to 15 bar resulted in approximately a 20% increase in maximum velocity and a 40–45% increase in vacuum pressure in the suction line. Among the investigated configurations, the nozzle diameter of 15 mm provided the most balanced flow structure, producing the highest pressure drop at the throat and the most stable suction behavior. Transient analyses revealed that suction formation occurs rapidly after flow initiation and remains stable throughout the operation period, indicating hydrodynamically stable injector performance under optimal conditions. The optimum operating point is identified as a nozzle diameter of 15 mm and an inlet pressure of 15 bar, where suction capacity is maximized and energy losses are minimized. The results provide a quantitative design guideline for the optimization of industrial Venturi injector system used in textile processing applications. Full article