Search Results (133)

High-resolution solar irradiance modelling over large 3D geospatial data is computationally demanding, and accounting for surface inter-reflection makes it even so. For computational efficiency it requires storing for every part of the surface, explicit knowledge of the other surfaces visible from it (its viewshed). The storage of each surface’s viewshed grows with both the dataset size and the angular resolution, and quickly becomes the dominant memory bottleneck. This paper presents a novel Graphics Processing Unit (GPU)-accelerated method for estimating solar potential over Digital Surface Models (DSMs) that model direct, diffuse and reflective irradiances. It keeps the viewshed information compact through a novel structurally lossless compression, i.e., a domain-specific encoding of remote sensing-derived visibility data that preserves exactly the visibility structure consumed by the radiative model, rather than a general-purpose integer coder. An ablation analysis over eight synthetic DSMs showed that the best compression scheme reached a compression ratio (CR) of up to ≈3.3, exceeding the general-purpose GPU baselines Binary Packing 32 and Elias-Fano on every dataset. On the largest DSM, whose $29.6$ GB uncompressed viewshed exceeds the 24 GB device memory, compression kept the data resident and reduced the runtime from $6.7$ h to $0.5$ h. Finally, the proposed method was applied to LiDAR (Light Detection and Ranging)-derived DSMs for four distinct locations, with the results demonstrating its high applicability. Full article

Raw mix-design variables used to predict ultra-high-performance concrete (UHPC) properties cannot fully represent internal proportions and structural compatibility. This study develops mechanism-informed proxy-core features based on particle packing, water film thickness, and rheology, and evaluates four feature systems using literature-derived datasets for compressive strength (924 samples), flexural strength (406 samples), and slump flow (192 samples). Eight regression models were compared using five-fold cross-validation, Bayesian optimization, SHAP, and ablation analysis. Proxy-W achieved an R² of 0.918 for compressive strength, only 0.005 higher than baseline-W on the original split. For flexural strength, baseline-WB achieved the highest R² (0.906), whereas proxy-W yielded the lowest MAE (2.140 MPa). The largest single-split difference occurred for slump flow (R²: 0.740 to 0.838 for W-based systems), but 30 repeated splits yielded mean R² values of 0.667 ± 0.169 and 0.738 ± 0.101 for baseline-W and proxy-W, respectively, while proxy-WB showed no average improvement over baseline-WB. Repeated and source-group validation further indicated that the predictive effects of proxy-core features were property-, representation-, partition-, and source-dependent. Overall, proxy-core features are best interpreted as physically informed relational representations rather than universally accuracy-enhancing features. Full article

Background/Objectives: Packing, flow, and aerosolization properties of a series of binary adhesive mixtures containing micronized or spray-dried drugs were investigated, and the relationships between these blend properties and the blend structure were studied. Methods: Micronized or spray-dried terbutaline sulfate and salbutamol sulfate were used as model drugs, and an α-lactose powder was used as the carrier. Binary mixtures with drug loads ranging from 2 to 20% were prepared. The bulk density, compressibility, permeability, and shearing properties of the carrier powder and mixtures were determined, along with the in vitro aerosolization propensity of the mixtures using two types of inhalers. Imaging of the mixtures was used to assess the blend structure. Conclusions: The particle engineering method gave differences in particle crystallinity and morphology. The development of the adhesive layer with drug load was broadly consistent with the blend state concept. Spray-dried particles, however, exhibited a higher propensity to localize within surface cavities on the carrier and produced a more voluminous enveloped adhesive layer. The spray-dried particles gave a higher bulk density, a lower Hausner ratio, comparable shear strength, and a lower angle of internal friction. Aerosolization performance, including metrics such as fine particle fraction (FPF), depended on inhaler design; nevertheless, for both inhalers, aerosolization behavior was influenced by blend state and physicochemical properties of the drug. At low drug loads, spray-dried particles dispersed to a lower degree, while at high drug loads, the dispersion performance of the two particle types converged. For example, at an intermediate drug load of 7.4%, the FPF was about 20% for the spray-dried drugs and about 30% for the micronized drugs using the Screenhaler device, while the corresponding FPF:s were about 25% and 50% for spray-dried drugs and 40% and 55% for crystalline drugs using the Monodose inhaler. Overall, the physical characteristics of the drug particles were found to influence the structural evolution of the blends, as well as their mechanical and aerosolization properties. Full article

To address the large model size, high computational cost, and limited deployment resources of keyword spotting models on edge platforms, this study proposes a collaborative multi-compression framework for lightweight deployment. Built on LiteKWS-Net, an attention-enhanced 2-D convolutional backbone, the framework combines adaptive importance-aware structured pruning, mixed-precision quantization, and quantization-aware multi-stage knowledge distillation. The retrained teacher reaches 97.90% (mean, 100,813 parameters, 0.385 MiB). MPDQ reaches 95.53 ± 1.16% at 8.27× theoretical weight compression. AIASP reaches 97.59% at a 30% target and 43.9% realized sparsity. The final joint model reaches 96.82% and, under ideal packed sparse mixed-precision storage, has a 51.55× theoretical weight-compression factor relative to the FP32 teacher; sparse-index overhead is excluded. On a Jetson Nano, the TensorRT FP16 network-body benchmark reports 2.86 ms latency and 0.69 mJ per inference. Full article

This study develops a finite element analysis (FEA) framework to quantify hydrostatic consolidation of ultra-high-molecular-weight polyethylene (UHMWPE) fibril arrays containing interstitial voids. Hexagonal and stochastic representative volume elements (RVEs) were constructed from experimentally measured fibril diameters and embedded in a nearly incompressible Mooney–Rivlin medium to transfer hydrostatic pressure to irregular fibril surfaces. Molecular dynamics (MD)-derived fibril properties at 300 K and 400 K were used to evaluate the effects of temperature, elastic–plastic deformation, and stochastic microstructure on void collapse and effective fiber properties. The 300 K elastic model required pressures approaching 1.3 GPa to reach approximately 1–2% void content, whereas the combined effects of elevated temperature, elastic–plastic fibril behavior, and stochastic fibril packing reduced the corresponding pressure to approximately 160 MPa. The stochastic RVE exhibited a higher initial void content, earlier plastic dissipation, lower initial effective stiffness, and nonuniform fibril–fibril contact evolution compared to the idealized hexagonal RVE. As void content decreased, both models converged toward the dense fibril response. The framework establishes a processing–microstructure–property relationship linking consolidation pressure to the evolving void morphology, fibril shape and contact development, and the resulting effective plane-strain bulk modulus and the transverse compressive stress–strain response, including the Young’s modulus and Poisson’s ratio, of UHMWPE fibers. Full article

Yellow River sediment is a promising resource for use in construction materials. However, the effects of Yellow River silt and sand in different applications remain unclear. This review examines the physicochemical properties of these two forms, their engineering applications, and the underlying mechanisms governing material performance. Yellow River sand is mainly used as a fine aggregate in conventional concrete, engineered cementitious composites (ECC), and cement mortar, whereas Yellow River silt is commonly used in subgrade fills, concretes incorporating multiple solid wastes, and building products. Across these applications, the behavior of Yellow River sediment in construction materials reflects both physical packing and chemical reactivity. Their relative contributions depend on sediment form, material system, processing condition, and sediment content. Chemical reactivity is observed mainly in systems containing Yellow River silt, although the contribution of the silt itself has not been isolated. In conventional concrete, the highest compressive strengths are generally observed when Yellow River sand replaces 10–30% of natural sand, but the exact level depends on mixture design. Regional differences in sediment composition further limit the direct transfer of this range and require evaluation based on target performance. Future research should develop predictive models linking sediment characteristics, content, and target performance, establish low-carbon activation methods, and clarify long-term durability under complex service conditions. Full article

This study explores sustainable construction by reusing two non-biodegradable wastes: synthetic human hair fiber (HHF) from wigs and toner waste (TW) from printing cartridges as partial cement mortar replacements. The mortar mixtures prepared using HHF (0–2%) and TW (0–20% cement substitution) were examined for compressive strength after 7, 14, and 28 days of curing. The response surface methodology (RSM) technique was employed to develop a mathematical relationship between different parameters and the response. The study shows that TW increases the compressive strength in moderation due to the fillers’ property and better packing of particles, whereas HHF decreases compressive strength due to poor dispersibility and low workability. The optimum mixture ratio (1.08% HHF + 10% TW) provided the highest compressive strength of 20.53 MPa at 28 days. Furthermore, the RSM model showed high prediction accuracy (R² = 0.9615). The study outcome shows that the research supports circular economy practices in the construction industry. Full article

High-Early-Strength Concrete (HESC) is increasingly required in accelerated construction, yet most existing studies focus on single nano-additives rather than hybrid waste-derived systems. This study investigates the individual and combined effects of nanoclay (NC), nanosilica (NS), and cellulose nanofibers (NCel)—each produced from industrial or agricultural waste—on the mechanical and microstructural properties of HESC. A Box–Behnken response surface methodology (RSM) design was employed to optimize nanomaterial dosages with respect to early-age compressive strength, while microstructural evaluation (SEM, EDS, elemental mapping) clarified the mechanisms of enhancement. The results demonstrate that NC, NS, and NCel play complementary roles in hydration acceleration, particle packing, pore refinement, and crack-bridging. The optimized hybrid system (1.64% NC, 0.115% NS, 0.027% NCel) achieved a 3-day compressive strength of 59.7 MPa, 7-day strength of 71.2 MPa, and 28-day strength of 94.6 MPa, representing increases of 42.14%, 36.92%, and 21.59%, respectively, over the control mixture. Microstructural observations confirmed matrix densification, reduced Ca/Si ratio (from 2.05 to 1.68), refined pore structure (<0.4 μm vs. 0.9–1.2 μm in control), and enhanced ITZ in the optimized mixtures. Statistical analysis yielded robust predictive models (R² = 0.977–0.996) with significant interaction terms confirming synergistic effects among the three nanomaterials. This work demonstrates that waste-derived hybrid nano-systems offer a sustainable and effective strategy for producing high-performance HESC, with the RSM-derived optimum providing balanced early- and later-age strength while maintaining practical feasibility for field implementation. Full article

Private information retrieval (PIR) enables a client to retrieve records from a server-hosted database without revealing the requested item. Most high-performance single-server PIR systems are optimized for exact index or keyword lookup, whereas controlled-vocabulary and structured-identifier applications may require a partially specified root-aligned prefix with per-position wildcards. This paper presents a stateless protocol for that restricted but practically relevant retrieval model. The construction combines a compact trie with leveled Brakerski–Gentry–Vaikuntanathan (BGV) homomorphic encryption, ciphertext–plaintext equality testing, single-instruction multiple-data (SIMD) packing, compressed-edge batching, and power-of-two slot rotations. The client stores no database-dependent hint, and the server stores no persistent client-specific evaluation material; all the query ciphertexts and required evaluation keys are uploaded in the online phase. We explicitly position the construction as a protocol-level integration for richer private retrieval semantics rather than as a new foundational PIR or homomorphic-encryption primitive. Security is formulated for an honest-but-curious single-query adversary under an explicit public leakage function covering trie topology, compressed-edge lengths, payload layout, query-upload shape, and the fixed response schedule. We further analyze broad wildcard queries: the match cardinality can reach the number of indexed keys, while the number of response ciphertexts is determined by public output capacity rather than by the private query. Experiments on three controlled synthetic datasets and one anonymized enterprise dataset show that compact trie compression and packed edge evaluation reduce server-side online latency relative to uncompressed and serial homomorphic baselines, with the largest gains on high-prefix-sharing workloads. The implementation achieves exact set-level agreement with a plaintext oracle at two wildcard densities while exposing an explicit trade-off among richer query semantics, stateless deployment, public structural leakage, and communication overhead. Full article

3D Gaussian Splatting (3DGS) has recently emerged as an effective representation for immersive 3D scene rendering, providing high visual fidelity and real-time rendering efficiency. To support interoperable compression of trained 3DGS content, the Moving Picture Experts Group (MPEG) is exploring Gaussian Splat Coding (GSC), which mainly targets already trained 3DGS models following the INRIA reference format. The current video-based GSC anchor reorders 3DGS attributes into 2D attribute maps using Parallel Assignment Linear Sorting (PLAS) and compresses the resulting maps using High Efficiency Video Coding (HEVC). However, higher-order spherical harmonic coefficients (SH-AC) often remain irregular and exhibit low local spatial correlation even after PLAS reordering, limiting the coding efficiency of conventional video codecs. This paper proposes a VQ-HEVC hybrid compression framework that is structurally compatible with the video-based GSC anchor framework, in which SH-AC coefficients are represented by vector quantization (VQ) indices, while the remaining attributes are encoded using the same HEVC-based procedure as the GSC anchor. The proposed method adopts a two-stage VQ scheme that combines coarse VQ and product-quantization-based residual quantization, together with zero-masked residual VQ and flexible PQ grouping, to improve index-map coding efficiency across rate points. The generated VQ indices are packed into YUV400 index-map sequences and encoded using HEVC lossless coding, while the corresponding codebooks are transmitted as metadata. Experimental results on the Bartender and Cinema sequences of the MPEG GSC CTC demonstrate consistent rate–distortion improvements over the video-based GSC anchor across multiple objective quality metrics within the evaluated setting. In terms of RGB-PSNR, the proposed method achieves BD-rate reductions of 22.3% and 18.5% for the Bartender and Cinema datasets, respectively. These results suggest that, for the evaluated GSC CTC sequences, VQ-based SH-AC representation can effectively complement PLAS-based video coding while maintaining consistency with the existing GSC coding structure. Full article

Properties of defects in crystals composed of soft particles, such as colloids, differ markedly from those in metals. In this work, dislocation reactions in a bundle of carbon nanotubes (CNTs) are investigated using relaxational molecular dynamics. The problem is reduced to a two-dimensional model, where the strain state of the CNT bundle is fully determined by the cross-sectional shapes of the nanotubes arranged in a close-packed triangular lattice. A pair of edge dislocations with opposite topological charges is introduced into an uniaxially compressed bundle, and their relaxational dynamics are analyzed as a function of the distance d between the parallel planes along which the dislocations glide. When the dislocations move in the same plane (d = 0), they annihilate, restoring a defect-free structure. For negative distances (d < 0), their interaction results in the formation of a vacancy (d = −1), a bivacancy (d = −2), extended voidions (d = −3, −4), or dislocation dipoles (d < −4). In contrast to metals, vacancy clusters containing more than two missing particles in CNT bundles relax into extended voidions. For positive distances (d > 0), the dislocation reaction generates interstitial-type defects in the form of crowdions, which at sufficiently large separations (d > 4) can also be interpreted as dislocation dipoles. In most cases, except for d = 0 and d = 1, dislocation glide enables complete relaxation of the initial shear strain, even in the presence of defects. However, for d = 0 and d = 1, dislocation annihilation or immobilization limits plastic deformation, resulting in only partial stress relaxation. The observed effects are due to the elliptization of the cross-sections of soft carbon nanotubes in the cores of defects. These findings highlight significant differences in defect behavior between crystals of deformable particles and conventional metallic systems. Full article

Freeze–thaw durability of 3D-printed engineered cementitious composites (3DP-ECC) is strongly affected by print-induced interlayer defects and anisotropy, particularly in cold regions. This study investigated Cast-ECC and Z-direction 3DP-ECC incorporating Yellow River sediment (YRS) as an equal-mass replacement for quartz sand at 0–100%. Compressive, three-point bending, and four-point bending tests, relative dynamic elastic modulus (RDME), XCT, MIP, SEM–EDS, and Weibull damage modeling were used to evaluate degradation up to 150 freshwater freeze–thaw cycles. Moderate YRS replacement (25–50%) improved particle packing, reduced visible defects, and refined the pore structure, thereby enhancing frost resistance. The R50 mixture showed the best residual performance: after 150 cycles, compressive strength decreased from 55 to 46 MPa in Cast-ECC and from 54 to 44 MPa in 3DP-ECC, corresponding to retention rates of 83.6% and 81.5%, respectively. The residual peak load in four-point bending of 3DP-ECC-R50 was 15.4% lower than that of Cast-ECC-R50, confirming the detrimental role of interlayer defects under loading perpendicular to the layers. RDME-based Weibull fitting described the overall damage evolution (R² = 0.876–0.994), while XCT, MIP, and SEM–EDS indicated that interlayer discontinuities, pore-structure evolution, and local microstructural degradation governed anisotropic deterioration. The results support durability-oriented design of YRS-based 3DP-ECC in cold regions. Full article

Short circuits and subsequent fires resulting from objects impacting the bottom of vehicle power battery packs considerably jeopardize electric vehicle (EV) operations. This study investigated underbody impacts in EVs and the overall mechanical properties of battery cells. Key features of road debris were extracted and simplified to establish a geometric parameter structure model and determine realistic battery pack responses to debris impact. Quasi-static compression and dynamic impact tests on a prismatic lithium-ion battery (LIB) and power battery pack followed. Macroscopic mechanical responses, deformation failure modes, and internal jellyroll damage of cells and packs were evaluated, and constitutive equations and failure parameters were derived to develop a finite element model, whose effectiveness and reliability were verified by comparing simulation results with experimental data. Finally, a homogenized model of the prismatic LIB and power battery pack was constructed, which effectively predicted the macroscopic mechanical response and internal short-circuit failure under mechanical loading. However, simulation and test results revealed certain deviations in cell indentations under battery pack bottom impacts, presumably because the FEMs neglect the dynamic strain rate effects of electrolyte and cooling liquid. Overall, this study elucidates safety risks to cells and their key components under power battery pack bottom impacts. Full article

Heterostructured metals and alloys are designed with spatial variations in strength and hardening that produce synergy beyond the rule of mixtures. This review surveys face-centered cubic (FCC), body-centered cubic (BCC), and hexagonal close-packed (HCP) systems, including architectures formed or modified by rolling and related severe plastic deformation routes, and examines them under tension, compression, and shear. Across material classes, mechanical incompatibility between hetero-zones drives stress partitioning and plastic strain gradients that store geometrically necessary dislocations near zone boundaries. The associated internal back and forward stresses sustain work hardening, delay instability, and influence localization and damage initiation. We evaluate continuum, crystal plasticity, dislocation-based mesoscale, and atomistic approaches by whether they predict these internal fields and whether they are validated against internal-field measurements. Key observations are that predictive models require physically identifiable intrinsic length scales, experimentally constrained interface laws, and careful separation of mechanisms to avoid double-counting when gradient and kinematic terms coexist. Major gaps remain in parameter identifiability for multi-zone and nonlocal formulations, in transferability across processing routes and loading modes, and in community benchmarks that couple well-characterized microstructures with multimodal measurements. Recommendations are provided for validation targets and benchmark campaigns to accelerate predictive design. Full article

Lightweight aggregates have a porous structure and high water absorption, which may lead to underestimation of the powder content in conventional mix design methods for lightweight ultra-high-performance concrete (LUHPC). To address this issue, this study used ceramsite sand as the lightweight aggregate and combined the excess paste theory with the particle packing method to design and evaluate ceramsite-sand-based LUHPC mixtures based on the modified Andreasen packing model (APM) and the compressible packing model (CPM). By optimizing the particle size distribution of ceramsite sand and the binder composition, a mix design method suitable for ceramsite-sand-based LUHPC was developed. The workability, apparent density, mechanical properties, elastic modulus, and shrinkage behavior of the material with different steel fiber contents were systematically investigated. The results showed that the total binder content, water-to-binder ratio, and paste volume of the mixtures designed using the two models differed only slightly. However, the aggregate skeleton formed by CPM was denser, and its skeleton packing volume was approximately 3.5% lower than that obtained using APM. At the same steel fiber content, the main mechanical properties of the CPM-designed LUHPC were generally superior to those of the APM-designed mixtures. Specifically, the 28-day cube compressive strength increased by 5.0–7.6%, the axial compressive strength by 8.8–12.2%, the axial tensile strength by 6.4–25.8%, the flexural strength by 14.1–17.2%, and the shear strength by 3.1–6.5%. The elastic modulus was also slightly higher, while the shrinkage remained consistently lower. The CPM-2.0 LUHPC mixture achieved a 28-day cube compressive strength of 124.6 MPa and an apparent density of approximately 1982 kg/m³, realizing a compressive strength above 120 MPa at a density below 2000 kg/m³. The 28-day cube compressive strength of the CPM-3.0 mixture further increased to 131.7 MPa. As the steel fiber content increased from 1.5% to 3.0%, the workability of LUHPC decreased, whereas its compressive, tensile, flexural, and shear properties generally improved, and the elastic modulus increased slightly. Steel fibers effectively restrained shrinkage deformation, but the improvement showed diminishing marginal benefits with increasing fiber content. Considering the mechanical performance, shrinkage control, and material economy, a steel fiber content of approximately 2.0% is recommended as a reference range for ceramsite-sand-based LUHPC. Overall, CPM is more suitable than APM for the mix design of ceramsite-sand-based LUHPC and can provide guidance for mix optimization and performance regulation of lightweight ultra-high-performance concrete. Full article