Specific Load Research Articles

Mesoscopic analysis on the coral aggregate reinforced concrete column under axial and eccentric compression

Coral aggregate concrete (CAC) has been identified as a promising building material for reef engineering construction, yet its practical application remains challenging due to incomplete research on the mechanical behaviors of the CAC beam and column components. In this study, a 3D mesoscale modeling approach considering the heterogeneity of CAC was utilized to investigate the mechanical performance of coral aggregate reinforced concrete columns (CARCCs) under axial and eccentric compression. Through numerical delineation of failure processes and damage mechanisms at the mesoscale, comprehensive parametric analysis integrating both numerical simulations and experimental validations were executed to assess the load-bearing capacity of CARCC. Results indicate that the mesoscale model has significant reliability in simulating the deformation and cracking failure behaviors and analyzing the load-displacement relationships of CARCC under axial and eccentric compression loads. When under axial loads, macroscopic cracks in CARCC primarily develop in an oblique manner, precipitating significant concrete spalling and extensive cracking failure along the longitudinal axis. Under eccentric loads, failure advances from crack initiation at load points to abrupt vertical fractures in stressed zones, manifesting a decrement in the load-bearing capacity with escalating eccentricity. Furthermore, the strength grade and reinforcement ratio exert a profound influence on the load-bearing capacity, with disparate impacts under varied loading conditions. It is concluded that reinforcement strategies tailored to specific loading conditions have significant implications for the design and safety of reinforced concrete structures in reef engineering projects.

Advancements in Biofiller-Reinforced PLA Composites for 3D Printing: A Review

Additive manufacturing is key in realizing highly complex and high-performance composite materials. Among all the various kinds of functionality that could be added to a composite component, continuous fiber-reinforced composites have been drawing much attention because of their attractive combination of properties. The comprehensive spectrum of knowledge that ranges from the basics concerned with structure, morphology, synthesis, physical, and chemical properties finally reaches to this analytical study of advanced composites. Most generally, such a composite is structured on a thermoplastic or thermoset polymer matrix that embeds the load-carrying reinforcing fibers; probably best known are carbon, glass, and aramid fibers. These composites, which involve fibers continuously reinforcing, have high strength relative to their weight. They are also anisotropic, meaning they have qualities that vary from one direction to another – something which might be customisable for specific load cases. They warp and shrink less during their life in an outside environment than conventionally made bioplastics due to a fact that short fibers can provide reinforcement to them. This 3-D printing object is manufactured by special additive manufacture technology during the manufacturing process after compounding and extruding the fiber-reinforced composite filament. The final properties of 3D printed parts could be tailorable through changing variables such a fiber type, fiber length, volume fraction, polymer matrix material, orientation of fibers, and printing process parameters. These continuous fiber-reinforced 3D printed composites could achieve tensile strengths up to one GPa, have stiffness values reaching even a rating of countless Gpa, and have ad thicknesses in the range from about 1.4–1.8 g/cm³. This finding could be applied in basically all major industries, from aerospace and the automotive industry to sports gear. Such conclusions from the analysis may be useful in the selection of appropriate materials and techniques while even guiding the development of new applications with respect to such advanced composite materials.

Design of photovoltaic and battery energy storage systems through load demand characterization: A case study in Thailand

The integration of photovoltaic (PV) system at behind the meter has gained popularity due to the growing trend toward environmentally friendly energy solutions. Coupling PV systems with battery energy storage systems (BESS) addresses the uncertainties of PV energy production while enhancing energy management. Load characteristics have influence on PV and BESS design both in technical and economic aspects. This paper presents a comprehensive analysis of load demand characterization methodologies tailored for the design of PV and BESS. The fundamental load properties such as daily maximum power, minimum power, and load energy, categorizing loads based on their daily and annual variation degrees are investigated. The techno-economic performance of PV-only and PV+BESS systems is analyzed, focusing on metrics such as excess energy, peak limiting performance, and economic feasibility using the levelized cost of energy (LCOE). The findings of this study reveal three distinct load characteristics based on daily variation: moderate (50–70 %), moderate to high (70–80 %), and high (80–90 %). Load profiles with moderate variation (50–70 %) demonstrate economic feasibility when sized with a PV-only system matching maximum power demand. With BESS prices reduced to less than 140 USD/kWh, these loads could also integrate a 1C-BESS sized at half capacity under the same control strategy, resulting in lower excess energy and LCOE. Conversely, loads with higher variation (>70 %) and lower self-consumption rates (<70 %) face fewer viable options for both PV-only and PV+BESS configurations, especially if BESS costs remain high. These loads require custom-designed solutions and more extensive load analysis. Through analysis, this study establishes the relationship between load characteristics and system design suitability for the loads studied. The findings underscore the importance of incorporating load demand characterization techniques in the design systems, highlighting the need for tailored approaches based on specific load characteristics and economic viability.

Analysis of the Construction Sequence of a Reaction Wall in a Structural Laboratory Supported by the VDC Methodology

The structures laboratory is a crucial facility for supporting research development related to the construction industry. This kind of laboratory has several components, and one of its key components is the reaction wall. The reaction wall supports the execution of experimental tests on structural elements under specific configurations and loads. Constructing a reaction wall presents challenges due to the highest standards to be met. This research analyzes the construction process of a reaction wall at a private university in Peru. Initially, a schedule was proposed by a contractor. However, the client, knowing the complexity of such construction, asked to review the initial schedule to ensure that it would meet the constructability requirements under the integrated product-organization-process approach given by the virtual design and construction (VDC) methodology. The result of this study pointed out the need to revise the original proposed schedule, extending the construction time to 66% due to the lack of construction processes compatible with the requirements for the reaction wall’s execution. Finally, a survey was conducted to observe the learning curve associated with implementing the VDC methodology.

Synergetic effect of in-situ TiB2 reinforcement and nano precipitation on wear behavior of ZE41 magnesium matrix composite

The rise in carbon dioxide pollution and energy consumption has increased the demand for lightweight materials such as magnesium in automotive and aerospace industries. However, magnesium alloys face challenges like poor wear resistance and mechanical strength. To overcome these limitations, a promising approach involves developing heterogeneous hybrid microstructures through reinforcement addition and microstructural engineering. This study focuses on the tribological performance of a newly developed in-situ sub-micron sized TiB2/ZE41 composite under various microstructural conditions, comparing it to the unreinforced ZE41 Mg alloy. Wear experiments were conducted using a pin-on-disc tribometer under normal loads of 10, 20, 40, and 60 N at a sliding velocity of 1 m/s. Scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS) was used to analyze the worn surfaces in order to identify damage types and surface distortions. By correlating worn surface microstructures with test parameters, predominant wear mechanisms for each material condition under specific loads were determined. Results consistently showed that the presence of in-situ TiB2 reinforcements, β-phase, and rare-earth precipitates enhanced wear resistance regardless of the load conditions. Additionally, the study established a scientific understanding of the wear behavior of ZE41 Mg alloy, with and without in-situ TiB2 particles and precipitates, through analysis of dominant wear mechanisms, wear-induced subsurface deformation mechanisms, kernel average misorientation, grain orientation spread, and microhardness evaluation.

Fatigue life prediction of CFRP flat-fold-flat adhesive joints

Taking the flat-fold-flat (FJF) adhesive joints of carbon fiber reinforced bismaleimide resin-based composite materials as the object, the regularized fatigue life model and residual stiffness model of the one-way plate and the cohesive model parameters of the adhesive layer were fitted experimentally, and based on this, the fatigue life of the adhesive joint was predicted by ABAQUS software. The results show that under specific maximum load conditions, the predicted cracking life of the adhesive layer at the end of the lap joint and the final fatigue life are not greater than the error values of the test results 3% , which has a relatively good calculation accuracy. The cracking life of the adhesive layer at the end of the lap joint is approximately equal to the final fatigue life of the adhesive joint, indicating that the cracking of the adhesive layer at the end of the lap joint accounts for the main part of the total life of the adhesive joint, and the crack propagation life of the adhesive layer can be ignored.

Impact of chronic ankle instability on gait loading strategy in individuals with chronic ankle instability: a comparative study

BackgroundLateral ankle sprains rank among the most prevalent musculoskeletal injuries, while chronic ankle instability (CAI) is its most common cascade. In addition to the conflicting results of the previous studies and their methodological flaws, the specific gait loading strategy is still not well studied.PurposeThe study aimed to investigate the fluctuations in gait loading strategy in people with chronic ankle instability compared to health control.MethodsA total of 56 male subjects participated in this study and were allocated into two groups: (A) CAI group: 28 subjects with unilateral CAI (age 24.79 ± 2.64 and BMI 26.25 ± 3.50); and (B) control group: 28 subjects without a history of ankle sprains (age 24.57 ± 1.17 and BMI 26.46 ± 2.597). Stance time, weight acceptance time, and load distribution were measured to investigate gait loading strategy.ResultsThe study findings revealed that the CAI group had a significant higher load over the lateral rearfoot. However, MANOVA indicates that there was no overall significant difference in gait loading strategy between the CAI and control groups. Furthermore, in terms of stance time, time of weight acceptance phase, load over medial foot, and load over lateral foot, CAI and healthy controls seemed to walk similarly.ConclusionsThe findings revealed that individuals with CAI had the significant alteration in the lateral rearfoot loading, suggesting a potential compensatory mechanism to address instability during the weight acceptance phase. This could manifest a laterally deviated center of pressure and increased frontal plane inversion during the early stance phase. However, it is acknowledged that these alterations could be both the result and the origin of CAI. The study highlights the vulnerability of CAI during the early stance phase, emphasizing the need for gait reeducation as individuals return to walking as healthcare clinicians should focus on treatment modalities aimed at reducing rearfoot inversion in individuals with CAI.

An efficient conditional GAN-based framework for high-resolution prediction of tyre-pavement contact stresses – a contribution towards a digital twin of the road system

ABSTRACT The high-resolution prediction of tyre-pavement contact stresses is crucial for advancing pavement design and vehicle safety. A significant knowledge gap exists in accurately and quickly predicting tyre-pavement contact stresses, especially under varying conditions. Addressing this challenge, this study is part of the concerted effort within the project CRC/TRR 339, contributing to the series ‘A Contribution towards a Digital Twin of the Road System’. It aims to bridge this gap by introducing a novel Multimodal Conditional Deep Convolutional Generative Adversarial Network (MC-DCGAN) model for forecasting tyre-pavement contact stresses, offering an efficient and accurate method. The incorporation of a multimodal conditional module within the GAN-based framework allows for controllable outputs tailored to specific tyre types, inflation pressures, and loads. Leveraging the DCGAN architecture significantly enhances prediction accuracy. Experimental validation confirms the method’s high accuracy, strong generalisation capabilities, and a substantial reduction in computational time – nearly two orders of magnitude lower compared to traditional Finite Element simulations. This research not only fills a critical void in the high-precision prediction of tyre-pavement contact stresses, but also holds significant implications for optimising pavement design and enhancing road traffic safety, marking a significant step towards realising a digital twin of the road system.

Fossil Diesel, Soybean Biodiesel and Hydrotreated Vegetable Oil: A Numerical Analysis of Emissions Using Detailed Chemical Kinetics at Diesel Engine Like Conditions

Nowadays, emissions from internal combustion engines are a relevant topic of investigation, taking into account the continuous reduction of emission limits imposed by environmental regulatory agencies around the world, obviously as the result of earnest studies that have pointed out the impact on the human health of high levels of contaminants released into the environment. Over recent years, the use of biofuels has contributed to attenuating this environmental issue; however, new problems have been raised, such as NOx emissions tend to increase as the biofuel percentage in the fuel used in engines increases. In this research, the emissions of a compression ignition internal combustion engine modeled as a variable volume reactor with homogeneous combustion were numerically investigated. To analyze the combustion process, a detailed kinetics model tailored specifically for this purpose was used. The kinetics model comprised 30,975 chemical reactions involving 691 chemical species. Mixtures of fuel surrogates were then created to represent the fuel used in the Brazilian fuel marketplace, involving (i) fossil diesel—“diesel A”, (ii) soybean diesel—“biodiesel”, and (iii) hydrotreated vegetable oil— “HVO”. Surrogate species were then selected for each of the aforementioned fuels, and blends of those surrogates were then proposed as mixture M1 (diesel A:biodiesel:HVO—90:10:0), mixture M2 (diesel A:biodiesel:HVO—85:15:0), and mixture M3 (diesel A:biodiesel:HVO—80:15:5). The species allowed in the kinetics model included all the fuel surrogates used in this research as well as the target emission species of this study: total hydrocarbons, non-methane hydrocarbons, carbon monoxide, methane, nitrogen oxides, carbon dioxide, soot, and soot precursors. When compared to experimental trends of emissions available in the literature, it was observed that, for all the proposed fuel surrogates blends, the numerical approach performed in this research was able to capture qualitative trends for engine power and the target emissions in the whole ranges of engine speeds and engine loads, despite the CO and NOx emissions at specific engine speeds and loads.

Evaluation of Static Displacement Based on Ambient Vibration for Bridge Safety Management.

The evaluation of bridge safety is closely related to structural stiffness, with dynamic characteristics and displacement being key indicators. Displacement is a significant factor as it is a physical phenomenon that bridge users can directly perceive. However, accurately measuring displacement generally necessitates the installation of displacement meters within the bridge substructure and conducting load tests that require traffic closure, which can be cumbersome. This paper proposes a novel method that uses wireless accelerometers to measure ambient vibration data from bridges, extracts mode shapes and natural frequencies through the time domain decomposition (TDD) technique, and estimates static displacement under specific loads using the flexibility matrix. A field test on a 442.0 m cable-stayed bridge was conducted to verify the proposed method. The estimated displacement was compared with the actual displacement measured by a laser displacement sensor, resulting in an error rate of 3.58%. Additionally, an analysis of the accuracy of displacement estimation based on the number of measurement points indicated that securing at least seven measurement points keeps the error rate within 5%. This study could be effective for evaluating the safety of bridges in environments where load testing is difficult or for bridges that require periodic dynamic characteristics and displacement analysis due to repetitive vibrations, and it is expected to be applicable to various types of bridge structures.

Adsorbent Properties of Porous Boron Nitride and Activated Carbon: A Comparative Study.

Porous boron nitrides possess beneficial properties such as high thermal and chemical stability which are critical for applications in adsorption processes. In order to assess possible fields of applications, trace-level adsorption isotherms of different hydrocarbons on two synthesized porous boron nitrides and two commercial activated carbons are compared. By normalizing the adsorptive loadings on the micropore surface area, superior adsorption performances of the BN materials on polar and aromatic adsorptives with up to 50% higher loadings compared to the activated carbons can be shown. Nonpolar adsorptives, on the other hand, feature higher specific loadings on the activated carbon. Consequently, the size of the micropore surface appears to be decisive for nonpolar adsorptives, while the higher polarity of the boron nitrides is the dominant influencing factor for the adsorption of polar and aromatic components. For an energetic study of the adsorbents, calorimetric experiments were performed to identify and discuss adsorbent-adsorptive interactions. While the initial heat of adsorption of the nonpolar n-hexane is lower on the boron nitride than on the activated carbon due to a less favorable spatial arrangement, toluene shows comparable values on both adsorbent classes and the polar acetone shows higher values on the polar boron nitride. Considering technical applications in adsorption technology, the thermal stability of the boron nitrides is investigated using spontaneous ignition temperatures and points of initial oxidation. Here, the porous boron nitrides with oxidation temperatures above 900 °C show about 400 °C higher values and thus a significantly higher thermal stability.

Understanding Solid Oxide Fuel Cell Hybridization: A Critical Review

A holistic literature review of 399 articles is presented on hybrid solid oxide fuel cell (SOFC) systems and taxonomized through a unique classification methodology that considers primary energy sources, component configurations, system outputs and relevant analysis. In the reviewed research articles, primarily four different types of technologies are used to complement the energy production of the fuel cell stack. As a result, four respective categories were established in terms of the coupling components, inclusive of (1) wind turbines (WTs), (2) solar systems (SS), (3) thermal power plant turbines (TPPTs) and (4) piston engines (PEs). Additional classification was needed to further subdivide the evaluated system configurations, due to the wide spectrum of system outputs encountered in the reviewed literature. That involved (a) electrical power generation (PG), (b) four types of cogeneration (CG), (c) four types of trigeneration (TG) and (d) two types of multigeneration (MG). Depending on the type of assessment in respective research, literature was further categorized as computational, experimental, or both computational and experimental. The most prevalent hybrid system amongst the 102 designs, as adapted from the reviewed literature, is the SOFC/gas turbine (GT) application, with the overwhelming majority producing exclusively electrical power output. The particular system is physically demonstrated in an existing 220-kW experimental facility established by the National Fuel Cell Research Center (NFCRC). The identified systems were predominantly computationally examined and research focused on operating conditions around specific design load ratings. Energy, exergy, economic, and environmental assessments were typically followed by sensitivity studies in the reviewed literature. The primary decision variables in most cases revolved around SOFC operating conditions, such as temperatures over 1000 °C as well as elevated pressures. Those resulted in the deterioration of the electrochemical cell and failed to be addressed by the majority of encountered studies. Improvements in the conversion efficiency of PG applications were enabled by natural gas (NG)-fed pressurized SOFCs, directly coupled to GTs. The most efficient power configuration in terms of thermodynamic performance was achieved by coupling PEs to SOFCs and a metal hydride reactor (MHR) to unlock a maximum net system efficiency of 79.54%. CG systems integrating solar cells (SCs) and photovoltaic panels (PVs) to SOFC subsystems can result in a combined efficiency of approximately 90% and sustain this over a broad energy demand range. TG systems incorporating gasifiers to SOFC/GT subsystems achieved a combined efficiency of 93%, whereas the optimal combined efficiency in MG configurations was identified at 79.5% by coupling SCs to the SOFC/GT/organic Rankine cycle turbine (ORCT) subsystems. In terms of cost-effectiveness, configurations that relied on increasing levels of renewable energy (RE) technologies resulted in high overall levelized cost of electricity (LCOE). This cost was increased further when power storage units were deployed to address wind and solar intermittency challenges. Configurations classified under TPPTs operating on low carbon-content fuels were preferred in terms of providing lower LCOE, while applications operating on gasified biomass and coal blends should deploy additional CO2 capture and storage units to mitigate respective emissions.

A cGAN-based fatigue life prediction of 316 austenitic stainless steel in high-temperature and high-pressure water environments

The thermo-mechanical-chemical coupling effect presents significant challenges in accurately predicting the fatigue life of 316 austenitic stainless steel in high-temperature and high-pressure water environments (referred to hereafter as environmental fatigue). The complexity of environmental fatigue experiments results in limited and dispersed data, further making the life prediction difficult. Traditional fatigue life prediction models are often constrained by specific loading conditions and do not adequately account for the complex environmental influences. To address these issues, this paper proposes a novel environmental fatigue life prediction model of 316 stainless steel utilizing conditional Generative Adversarial Networks. The proposed model incorporates critical environmental factors, loading conditions and stacking fault energy, allowing direct prediction of environmental fatigue life. A comparative analysis on the predicted and experimental results reveals that the cGAN-based model significantly improves the prediction accuracy, reducing the fatigue life prediction error from a factor of 5 to within 3. To quantify the uncertainty in fatigue life prediction, the Monte Carlo Dropout method is employed to enable a probabilistic assessment of fatigue life. Furthermore, four environmental and loading conditions are established to evaluate the model’s extrapolation capability. The results demonstrate that the probabilistic fatigue assessment effectively captures data distribution and achieves high prediction accuracy.

Structural System and Computational Dynamic Model of a Life-Saving Multi-Storey Building with a Kinematic Seismic Isolation System

Introduction. In design of a life-saving multi-storey building, a seismic isolation system in the form of the kinematic supports is used to ensure the seismic resistance and reduce the seismic loads. The structural system, the computational dynamic model and the results of the intermediate in-situ tests of a life-saving multi-storey building with a kinematic seismic isolation system being built in Grozny have been analysed in the article.Materials and Methods. The research included modeling and computation of the structural system of a building with a kinematic seismic isolation system. In-situ tests were carried out to confirm the working capacity of the seismic isolation system connections.Results. A multi-storey life-saving building was designed according to a frame-core wall structure, where the vertical load-bearing elements were core walls, columns and connections between the columns in the form of the stiffening diaphragms. The high-rise part of a building was designed using a kinematic seismic isolation system consisting of the seismic isolating concrete-filled steel tubular supports. The results of the calculations of the main and specific load combinations and internal forces in the load-bearing structures have been presented.Discussion and Conclusion. The research has shown that the use of the developed structural system of seismic isolation with kinematic supports makes it possible to reduce the seismic loads and the total weight of a building and at the same time to increase its mechanical reliability and safety. The conducted intermediate in-situ tests have confirmed the working capacity of the joints connecting the supports with the monolithic reinforced concrete structures of a building, which makes it possible to implement the kinematic seismic isolation supports into the construction industry practices.

Increasing the prediction quality of artificial neural network–based optimisation approaches for the sheet moulding compound compression moulding process by means of targeted expansion of training data

The resulting fibre orientation when pressing Sheet Moulding Compound (SMC) is essentially dependent on the position and geometry of the resin mat in the mould. It is desirable to adapt the fibre orientation as best as possible to best withstand the applied load. The relationship between the position and geometry of the resin mat and the deflection of the final part under a specific load can be mapped using a numerical simulation; nevertheless, an optimisation is not feasible based on the simulation in an economically reasonable time frame due to the required computing time. For this reason, a metamodel based on an ensemble of artificial neural networks (ANN) was created on the basis of the simulation data, and an optimisation based on these ANN was set up. However, the investigations show that the minimal deflections found on the basis of the metamodel through optimisation have large deviations compared to the simulation. This leads to the hypothesis that the applied optimisation finds weak points of the metamodel instead of actual minima. From this hypothesis, an extension approach of the data set on which the metamodel is based by the weak points found is derived and implemented. This is done in an iterative process. The results show that the goal of increasing the prediction quality of the optimisation approach is achieved by the developed approach. The root mean square error (RMSE) could be reduced from the original deflection of 25 to 7 mm, which corresponds to a reduction of 72%. It is shown that the presented approach is successful in increasing prediction quality; nevertheless, further measures are needed to reach decent prediction quality.

Simulation and performance characteristics of rock with borehole using Visual Finite Element Analysis

Purpose. This study aims to investigate fluid flow and heat transfer within rocks containing boreholes, focusing on the complex mechanisms within hot reservoirs. Non-commercial finite element (FE) software is used to visualize and present the results. Methods. The study involved the use of FE method with Visual Finite Element Analysis (VisualFEA) software to analyze the coupled phenomena of fluid flow and heat transfer in a rock sample. Special attention was given to incorporating material structure and geotechnical analysis in the software, as well as the treatment of cracked elements. In addition, the validation was done by comparing the current numerical solution using VisualFEA with the numerical solution using ANSYS Software. Findings. The study findings highlight the capabilities of VisualFEA software to accurately represent fluid flow, stress, and heat transfer in borehole-containing rocks. The results include insights into flow direction within the borehole, temperature distribution, and the validation of the software performance against expected system behavior. The study demonstrates the effectiveness of VisualFEA in handling complex loading and its ability to visualize multiple flow directions within a 2D model. The results are presented in the form of contours and curves. Originality. This study contributes to the field demonstrating the application of VisualFEA software in analyzing fluid flow and heat transfer in rocks with boreholes. The focus on incorporating material structure, geotechnical analysis, and treatment of cracked elements adds originality to the study, providing a comprehensive understanding of the coupled phenomena in hot reservoirs. Practical implications. The practical significance of this study is in the validation and benchmarking of VisualFEA software for studying fluid flow and heat transfer in geotechnical application. The findings can be utilized by geotechnical engineers and researchers to better understand the behavior of borehole-containing rocks under specific pressure and thermal loading conditions. The insights gained from this study can be used in decision-making processes related to resource mining, reservoir engineering, and geothermal energy use.

Development of functionally graded structure for hip endoprosthesis stem based on lattice-type metamaterial

The paper reports on design and studies of a promising configuration of a hip endoprosthesis stem. The femoral component of the endoprosthesis is constructed based on a metamaterial produced by additive technologies, representing a periodic porous structure of variable topology. The central goal of the design procedure was to numerically determine the spatially graded relative density of the lattice structure within the implant volume by solving the optimization problem. The first stage of development comprised finite element modeling of a system with a solid implant attached, i.e., the optimization space, for seven different loading scenarios. These scenarios were constructed to represent the most typical cases of human motor activity. The second step was to determine the optimal spatial distribution of relative density of the lattice structure in the implant volume, obtained by solving the topological optimization problem under the given loading. After the optimization problem was solved, the distribution of the relative density of the lattice structure was obtained, serving as a basis for constructing a geometric model of a functionally graded porous scaffold for implantation. This result allows achieving an optimal ratio of stiffness and mass properties under the given loading conditions. The approach was verified by direct finite element modeling of the constructed lattice geometry of the implant under specific loading scenarios. Analyzing the stress fields in the volume of the endoprosthesis, we concluded that there were no critical regions in the developed structure, so the approach taken to develop the metamaterial-based endoprosthesis can be deemed correct.

Regional analysis of specific suspended sediment loads in northern Iran using multivariate statistical techniques

ABSTRACT Predicting suspended sediment loads in areas without detailed measurements, or with only short-term records, is crucial for the sustainable management of water resources. This study aimed to establish the relationships between specific suspended sediment loads and the characteristics of 23 sub-basins within the Haraz-Neka River basin, in Iran, to create regional models to estimate the sediment loads. To achieve this, several analytical methods were used, including cluster analysis, principal component analysis, principal component and classification analysis, and general linear modelling. Among these, the principal component analysis regression model was the most effective for estimating suspended sediment loads in the clusters. The principal component and classification analysis revealed that the best predictor was the first principal component, which strongly correlated with the minimum and mean elevation of the sub-basins. The general linear model regression showed the best overall performance for estimating regional suspended sediment loads in the study area.

Acute effects of cold, heat and contrast pressure therapy on forearm muscles regeneration in combat sports athletes: a randomized clinical trial.

Due to the specific loads that occur in combat sports athletes' forearm muscles, we decided to compare the immediate effect of monotherapy with the use of compressive heat (HT), cold (CT), and alternating therapy (HCT) in terms of eliminating muscle tension, improving muscle elasticity and tissue perfusion and forearm muscle strength. This is a single-blind, randomized, experimental clinical trial. Group allocation was performed using simple 1:1 sequence randomization using the website randomizer.org. The study involved 40 40 combat sports athletes divided into four groups and four therapeutic sessions lasting 20min. (1) Heat compression therapy session (HT, n = 10) (2) (CT, n = 10), (3) alternating (HCT, n = 10), and sham, control (ShT, n = 10). All participants had measurements of tissue perfusion (PU, [non-reference units]), muscle tension (T-[Hz]), elasticity (E-[arb- relative arbitrary unit]), and maximum isometric force (Fmax [kgf]) of the dominant hand at rest (Rest) after the muscle fatigue protocol (PostFat.5min), after therapy (PostTh.5min) and 24h after therapy (PostTh.24h). A two-way ANOVA with repeated measures: Group (ColdT, HeatT, ContrstT, ControlT) × Time (Rest, PostFat.5min, PostTh.5min, Post.24h) was used to examine the changes in examined variables. Post-hoc tests with Bonferroni correction and ± 95% confidence intervals (CI) for absolute differences (△) were used to analyze the pairwise comparisons when a significant main effect or interaction was found. The ANOVA for PU, T, E, and Fmax revealed statistically significant interactions of Group by Time factors (p < 0.0001), as well as main effects for the Group factors (p < 0.0001; except for Fmax). In the PostTh.5min. Period, significantly (p < 0.001) higher PU values were recorded in the HT (19.45 ± 0.91) and HCT (18.71 ± 0.67) groups compared to the ShT (9.79 ± 0.35) group (△ = 9.66 [8.75; 10.57 CI] > MDC(0.73), and △ = 8.92 [8.01; 9.83 CI] > MDC(0.73), respectively). Also, significantly (p < 0.001) lower values were recorded in the CT (3.69 ± 0.93) compared to the ShT (9.79 ± 0.35) group △ = 6.1 [5.19; 7.01 CI] > MDC(0.73). For muscle tone in the PostTh.5m period significantly (p < 0.001) higher values were observed in the CT (20.08 ± 0.19Hz) group compared to the HT (18.61 ± 0.21Hz), HCT (18.95 ± 0.41Hz) and ShT (19.28 ± 0.33Hz) groups (respectively: △ = 1.47 [1.11; 1.83 CI] > MDC(0.845); △ = 1.13 [0.77; 1.49 CI] > MDC(0.845), and △ = 0.8 [0.44; 1.16 CI], < MDC(0.845)). The highest elasticity value in the PostTh.5m period were observed in the CT (1.14 ± 0.07) group, and it was significantly higher than the values observed in the HT (0.97 ± 0.03, △ = 0.18 [0.11; 0.24 CI] > MDC(0.094), p < 0.001), HCT (0.90 ± 0.04, △ = 0.24 [0.17; 0.31 CI] > MDC(0.094), p < 0.001) and ShT (1.05 ± 0.07, △ = 0.094 [0.03; 0.16 CI] = MDC(0.094), p = 0.003) groups. For Fmax, there were no statistically significant differences between groups at any level of measurement. The results of the influence of the forearm of all three therapy forms on the muscles' biomechanical parameters confirmed their effectiveness. However, the effect size of alternating contrast therapy cannot be confirmed, especially in the PostTh24h period. Statistically significant changes were observed in favor of this therapy in PU and E measurements immediately after therapy (PostTh.5min). Further research on contrast therapy is necessary.

Realization of Friction Stir Welding of Aluminum Alloy AA5754 Using a Ceramic Tool

When engaging in the friction stir welding of aluminum/aluminum joints, the conventional use of tools made of hard metal and steel involves a complex and costly production process. These tools experience wear over welding distances and require frequent replacement to ensure the consistency of the welded seams. The exploration of silicon nitrite as a tool material emerges as a promising alternative in this scenario. The heightened hardness of non-oxide ceramics anticipates a diminished wear rate compared to traditional welding materials, translating into an extended operational lifespan. Nevertheless, the adoption of ceramics introduces challenges initially perceived as detrimental to friction stir welding. The inherent brittleness of silicon nitrite makes it susceptible to breakage under specific loads, and thermal stresses within the component can lead to failure. To mitigate these vulnerabilities, a ceramic material with high thermal shock resistance and a low proportion of sintering additives was used. Employing these accurately designed tools friction stir welding (FSW) was performed on sheets of AA5754, followed by a comprehensive examination of their microstructural and mechanical properties. It was demonstrated that a joint efficiency of 88% can be achieved, and that an increase in hardness within the stir zone occurred as a consequence of grain refinement. Furthermore, the Portevin–Le Chatelier effect, which is characteristic of this alloy, was influenced by the FSW process.