Load Shape Research Articles

Design and research of the ground robotic system structure for weapons remote control

During hostilities, ground robotic systems play an important role in minimizing losses of servicemen and suspending the combat capabilities of troops. For firing, robotic complexes are equipped with gun turrets. Researchers are conducting research to improve the performance, reliability and firing accuracy of such turrets. This work describes the design and research of an experimental sample of a ground robotic system, which is equipped with a turret for controlling the position of a machine gun. The description and results of experimental studies of dynamic loads during robot movement at different speeds and road conditions are presented. It was established that the values of the maximum accelerations that must be worked out by the stabilization system during operation for the experimental design of the robot do not exceed 20 rad/s2. The possibility of using counterweights was considered to reduce the torque of the turret guidance drive while reducing the dimensions of the robotic system structure. The description of the experimental module equipped with a control and measurement system and the results of experimental studies on determining the power of the turret drives during the manipulation of the structure are presented. A procedure of dynamic analysis and the results of modeling the movement of the gun turret in the ANSYS software package are presented. The proposed method for designing the structure ensures the determination of the impact on the structure of the complex shape of loads caused by its manipulation, to compensate for the exciting loads when the robotic system is moved over the terrain. With the help of this method, it is possible to determine and minimize the power, and therefore the energy consumption, of azimuth and lifting electric drives at the design stage

2d Models of Steel Beams under Patch Loading for Buckling Coefficient Assessment

This paper proposes an equivalent 2d model incorporating translational and rotational springs to simulate constraints in the stability analysis of steel plates under in-plane patch loading. The main objective is to develop an equivalent stability analysis of these plates by accurately calibrating the level of constraint provided by the stiffeners and flanges. The calibration involves determining the spring constants of a 2d equivalent plate model to achieve the same linear elastic critical load and buckled shape as a 3d model. The paper uses the buckling coefficient as the objective function to calibrate the translational and rotational springs. The ultimate goal is to effectively replicate the constraint conditions imposed by the flanges and vertical stiffeners within the structure. The proposed simplified method yields results that closely align with those obtained from the original 3d model, incorporating finite-rigidity restraints.

Optimal Allocation and Energy Management of Units in Distribution Networks with Multiple Renewable Energy Sources and Battery Storage Based on Computational Intelligence

The paper deals with an optimization problem in an electricity distribution network with different types of distributed generation and a battery storage system in terms of a smart grid concept. The optimization problem considers two objectives, namely, the annual energy losses and the exchange of energy with the higher-level power grid. The decision variables of the problem are the allocation of the different distributed generation units and the battery storage system, the annual power profiles of the controllable distributed generation and the battery storage system, and the power factor profiles of the controllable and noncontrollable distributed generation. All decision variables are solved simultaneously in a single optimization problem. The variable load shapes of the grid consumers and the profiles of the photovoltaic and wind power systems are considered in the study. All data are observed at the annual level with hourly resolution. The problem solving method uses computational intelligence techniques, namely, metaheuristic optimization methods and artificial neural networks. The study proposes a framework for optimizing the decision variables in the planning phase of distributed generation and battery storage, and for controlling the variable power and power factor profiles based on an artificial neural network in the implementation phase. The optimization problem is solved with a power system simulation program and a metaheuristic optimizer in cosimulation synergy. The three cases of distributed generation and battery storage are considered simultaneously. The proposed method is applied to the test grid operator IEEE with 37 buses, and reductions in annual energy losses and energy exchange are obtained in the ranges 34–86% and 41–99%, respectively.

Snow Load Shape Coefficients and Snow Prevention Method for Stepped Flat Roofs

Excessive snow load and nonuniform snow deposition are the main factors leading to building collapses. The snow load shape coefficient represents the dimensionless snow load, and its value is related to the unbalanced distribution of snow. The snow load shape coefficients for stepped flat roofs vary greatly in the codes of different regions, which always leads to underestimation of snow loads. We need a widely used standard for snow load shape coefficients. Therefore, through a combination of field measurements and numerical simulations, this study probes the snow accumulation processes and snow load shape coefficients on stepped flat roofs and proposes an equation to calculate snow load shape coefficients and the optimal slope of snow protection for lower roofs. It is found that the maximum snow load shape coefficient emerges at the roof junction with a value of 3.44. The nonuniform length of the snow accumulation is equal to two times the level difference. Based on these, the equation of the snow load shape coefficients is summarized, which is combined with the discrepancies between different codes and the regularity of snow distributions. In this study, the dynamic grid technology under the Eulerian framework is used to successfully predict snow accumulation on stepped flat roofs, and it is noted that snow erosion and deposition are closely related to the location and size of vortexes. Finally, we consider that the ideal slope for the lower roof to prevent snow should be 11°.

Cross-linking degree modulation of 4D printed continuous fiber reinforced thermosetting shape memory polymer composites with superior load bearing and shape memory effects

While 4D printing technology can effectively simplify the manufacturing process of complex spatially deployable structures and improve material utilization, its sustainable development still faces challenges due to the inferior mechanical load bearing properties of the printed materials. In this study, continuous fiber-reinforced thermosetting shape memory polymer (CF/Ts-SMP) 4D printing technology was employed to attain superior load bearing and shape memory functions of structures. The mechanism of Ts-SMP cross-linking degree on the printing rheological, thermomechanical, mechanical load bearing and shape memory properties of composites was investigated. With 5 % curing agent content, the 4D printed CF/Ts-SMP composites was in moderate cross-linking degree and showed superior overall mechanical and shape memory properties, with a bending strength of 806.38 MPa, a flexural modulus of 47.2 GPa, a shape fixation ratio of 98.46 %, and a shape recovery ratio of 99.01 %. Based on this, complex sandwich pod structure was further printed, which have potential future applications in the fields of space-deployable structural hinges and robot deformable joints.

Buckling Analysis of a Thin-Walled C-Section Channel under Mechanical and Thermal Load

Buckling analysis of thin-walled structures is essential to ensure their structural integrity under various loading conditions. The study aims to analyse buckling in thin-walled structures, particularly a C-section channel, under different loads, considering cases with and without holes, using FEM. It investigates hole impact on buckling, critical load, and mode shapes, offering insights for C-section channel design. A finite element method (FEM) is used to model the structure and simulate mechanical and thermal loading conditions. Additionally, the study investigates the critical buckling load factor and mode shapes for both cases with and without holes. The results show that the presence of holes significantly affects the buckling behaviour of the structure. The mode shapes indicate that the buckling behaviour of the structure is different for each case. The critical buckling load factor is lower for the C-section channel with holes, indicating a higher risk of buckling. The results of this study provide insights into the buckling behaviour of thin-walled structures and demonstrate the importance of considering the presence of holes in the design and optimization of C-section channels.

Daylight saving all year round? Evidence from a national experiment

We study the effects of staying on daylight saving time (DST) permanently on electricity consumption, generation, and emissions. In October 2016, Turkey chose to stay on DST all year round. Employing alternative identification methods, we find a negligible overall impact on consumption. However, the policy has a strong intra-day distributional effect, increasing consumption in the early morning and reducing it in the late afternoon. This change in the load shape reduced generation by dirtier fossil fuel plants and increased it by cleaner renewable sources that can more easily satisfy peak load generation. Emissions from generation decreased as a result. A large presence of hydropower, which is a reliable provider of energy to the grid in peak times, was crucial to achieve this reduction.

Fuzzy inference system model for the spectrum characteristic periods of the Türkiye Building Earthquake Code (2007)

Seismic design codes define response spectra with crisp numerical classifications of seismic parameters, which mainly affect the spectrum's shape and determination of seismic design loads. The efficiency of structural safety and construction costs depends on the optimum design and accurately determined seismic forces. As presented in the seismic design codes, several parameters are utilized to calculate the seismic design forces with response spectra. This study proposes a rule-based fuzzy inference system (FIS) model with fuzzy set numbers to determine the relevant parameters. By defining the soil profile thickness and shear wave velocity as inputs, the model generates the spectrum characteristic periods specified in the Türkiye Building Earthquake Code (TBEC 2007). The response spectra of twenty different samples with the FIS and crisp models were generated and compared to assess the model's superiority. Unlike crisp seismic code classifications, the proposed FIS model accounts for imperfections in soil group selection and topmost soil layer thickness, offering a more realistic representation of uncertainties and proving to be an effective tool for addressing linguistic vagueness in seismic response spectra analysis. The comparison between fuzzy and crisp output seismic parameters revealed significant differences in response spectra shape and spectrum intensity values. The FIS model-generated spectra were more conservative in certain building locations, while in others, they provided similar or lower values, suggesting potential cost savings in design. The FIS model demonstrates its efficacy in producing more accurate and robust designs by considering the uncertainties inherent in the problem. Furthermore, this approach has the potential to be extended to study seismic parameters of other design codes, although further research is required to comprehensively explore its capabilities and limitations.

EFFECTS OF WIND SPEED AND MOUNTING TYPE ON PV MODULE IN UNBALANCED DISTRIBUTION SYSTEMS

This paper assesses the effects of wind speed and mounting type on the performance of photovoltaic (PV) modules in the three phase unbalanced IEEE 34 node distribution system. The study was conducted in OpenDSS considering ZIP load model and residential load shape. The module temperature was calculated considering the wind speed and mounting type of the PV panel. The impact of wind speed on PV has been analyzed using three different wind data sets. Furthermore, free standing and flat roof mounting types were considered to evaluate the effect of mounting configuration. It was found that integrating PV into the distribution system reduced substation demand and energy losses. Results also show that the PV produced more power in high wind speed scenarios than in low wind speed scenarios. Regarding the mounting configuration, the PV incorporated with free standing configuration generated more power than the flat roof mounting type.

Evaluation of embrittlement of construction steels by microindentation

The mechanical characteristics of a metal are determined by a combination of three groups of factors: the chemical composition, structural features and the deformation ability of the structure, i.e., the ability of elements to relax internal stresses during deformation through dislocation sliding which does not lead to the crack formation and destruction. The possibility of using microindentation to assess the deformation ability of the structure of structural steels with a relatively high ductility is the goal of the study. The theoretical analysis revealed that an increase in the stiffness and a decrease in the plasticity of a metal leads to a change in the deformation model during indentation and, in particular, to the occurrence of deformation effects of various morphologies on the surface near the imprint, which can be indicative of the metal plasticity. Experimental studies performed on pipe steels of various strength and types of the structure confirmed that as the deformation ability of the metal decreases (primarily as a result of deformation hardening), a system of localized shears is formed near the imprint along the lines of action of maximum tangential stresses. A scale for ranking data of localized shears is proposed and the optimal load value and shape of the indenter are determined which provide gaining maximum information by microindentation. A methodology for assessing the embrittlement of plastic construction steels based on the results of microindentation has been developed, which can form a basis for creating an effective technology of nondestructive evaluation of the metal state.

A Flexible Regression Modeling Approach Applied to Observational Laboratory Virological Data Suggests That SARS-CoV-2 Load in Upper Respiratory Tract Samples Changes with COVID-19 Epidemiology.

(1) Background. Exploring the evolution of SARS-CoV-2 load and clearance from the upper respiratory tract samples is important to improving COVID-19 control. Data were collected retrospectively from a laboratory dataset on SARS-CoV-2 load quantified in leftover nasal pharyngeal swabs (NPSs) collected from symptomatic/asymptomatic individuals who tested positive to SARS-CoV-2 RNA detection in the framework of testing activities for diagnostic/screening purpose during the 2020 and 2021 winter epidemic waves. (2) Methods. A Statistical approach (quantile regression and survival models for interval-censored data), novel for this kind of data, was applied. We included in the analysis SARS-CoV-2-positive adults >18 years old for whom at least two serial NPSs were collected. A total of 262 SARS-CoV-2-positive individuals and 784 NPSs were included: 193 (593 NPSs) during the 2020 winter wave (before COVID-19 vaccine introduction) and 69 (191 NPSs) during the 2021 winter wave (all COVID-19 vaccinated). We estimated the trend of the median value, as well as the 25th and 75th centiles of the viral load, from the index episode (i.e., first SARS-CoV-2-positive test) until the sixth week (2020 wave) and the third week (2021 wave). Interval censoring methods were used to evaluate the time to SARS-CoV-2 clearance (defined as Ct < 35). (3) Results. At the index episode, the median value of viral load in the 2021 winter wave was 6.25 log copies/mL (95% CI: 5.50-6.70), and the median value in the 2020 winter wave was 5.42 log copies/mL (95% CI: 4.95-5.90). In contrast, 14 days after the index episode, the median value of viral load was 3.40 log copies/mL (95% CI: 3.26-3.54) for individuals during the 2020 winter wave and 2.93 Log copies/mL (95% CI: 2.80-3.19) for those of the 2021 winter wave. A significant difference in viral load shapes was observed among age classes (p = 0.0302) and between symptomatic and asymptomatic participants (p = 0.0187) for the first wave only; the median viral load value is higher at the day of episode index for the youngest (18-39 years) as compared to the older (40-64 years and >64 years) individuals. In the 2021 epidemic, the estimated proportion of individuals who can be considered infectious (Ct < 35) was approximately half that of the 2020 wave. (4) Conclusions. In case of the emergence of new SARS-CoV-2 variants, the application of these statistical methods to the analysis of virological laboratory data may provide evidence with which to inform and promptly support public health decision-makers in the modification of COVID-19 control measures.

Establishing gaze markers of perceptual load during multi-target visual search

Highly-automated technologies are increasingly incorporated into existing systems, for instance in advanced car models. Although highly automated modes permit non-driving activities (e.g. internet browsing), drivers are expected to reassume control upon a ‘take over’ signal from the automation. To assess a person’s readiness for takeover, non-invasive eye tracking can indicate their attentive state based on properties of their gaze. Perceptual load is a well-established determinant of attention and perception, however, the effects of perceptual load on a person’s ability to respond to a takeover signal and the related gaze indicators are not yet known. Here we examined how load-induced attentional state affects detection of a takeover-signal proxy, as well as the gaze properties that change with attentional state, in an ongoing task with no overt behaviour beyond eye movements (responding by lingering the gaze). Participants performed a multi-target visual search of either low perceptual load (shape targets) or high perceptual load (targets were two separate conjunctions of colour and shape), while also detecting occasional auditory tones (the proxy takeover signal). Across two experiments, we found that high perceptual load was associated with poorer search performance, slower detection of cross-modal stimuli, and longer fixation durations, while saccade amplitude did not consistently change with load. Using machine learning, we were able to predict the load condition from fixation duration alone. These results suggest monitoring fixation duration may be useful in the design of systems to track users’ attentional states and predict impaired user responses to stimuli outside of the focus of attention.

A data-driven analytic approach for investigation of electricity demand variability for energy conservation programs

Targeting and designing effective demand response and energy efficiency strategies is a challenging task owing to the variations in electricity usage patterns. To address this problem, we attempt to propose a clustering and Kullback-Leibler (KL) Divergence-based solution to understand the variability across the different consumption patterns. The proposed unsupervised approach utilized hierarchical clustering technique for segmenting the customers based on the similarity in their consumption behaviour, followed by the incorporation of the KL divergence to quantify the variability for different features of customer's load profiles. These features aid in understanding the diversity in load shapes. Depending on the different features, the results reveal that a few of the consumers having certain distinctive consumption can be easily considered as potential for demand flexibility, while others require careful consideration for program offerings. The result also shows significantly higher day-to-day variations in the clustered groups and can be managed by designing suitable behavioural modification strategies. The variability assessment of individual customer profiles helps better comprehend the diversity in usage behaviour. It leads to informed decision-making in planning demand response and energy efficiency initiatives, which was not taken into consideration in the previous studies.

Targeted demand response for flexible energy communities using clustering techniques

The present study proposes clustering techniques for designing demand response (DR) programs targeting commercial and residential prosumers. The goal is to alter the consumption behavior of the prosumers within a distributed energy community in Italy. This aggregation aims to: (a) minimize the reverse power flow at the primary substation, occurring when generation from solar panels in the local grid exceeds consumption, and (b) shift the system wide peak demand, that typically occurs during late afternoon. Regarding the clustering stage, we consider daily prosumer load profiles and divide them across the extracted clusters. Three popular machine learning algorithms are employed, namely k-means, k-medoids and agglomerative clustering. We evaluate the methods using multiple metrics including a novel metric proposed within this study, namely peak performance score (PPS). The k-means algorithm with dynamic time warping distance considering 14 clusters exhibits the highest performance with a PPS of 0.689. Subsequently, we analyze each extracted cluster with respect to load shape, entropy, and load types. These characteristics are used to distinguish the clusters that have the potential to serve the optimization objectives by matching them to proper DR schemes including time of use, critical peak pricing, and real-time pricing. Our results confirm the effectiveness of the proposed clustering algorithm in generating meaningful flexibility clusters, while the derived DR pricing policy encourages consumption during off-peak hours. The developed methodology is robust to the low availability and quality of training datasets and can be used by aggregator companies for segmenting energy communities and developing personalized DR policies.

Effect of Ovality on the Buckling Behavior of Thin-Walled Liquid-Filled Conical Tanks

This study investigates the influence of ovality on the buckling behavior of thin-walled liquid-filled conical tanks through comprehensive numerical simulations. The structural stability of conical tanks is of paramount importance in various engineering applications, such as storage vessels and aerospace structures. However, the presence of ovality, characterized by deviations from perfect circularity, can significantly affect the structural response and integrity of these tanks. To explore the effects of ovality, a finite element analysis (FEA) approach is employed, considering various ovality levels in the tank geometry. A comprehensive parametric study is conducted, varying key parameters such as tank dimensions, material properties, and liquid filling levels. The buckling behavior of the tanks is assessed by examining critical buckling loads and corresponding deformation modes. Results from the numerical simulations reveal that even small levels of ovality can substantially reduce the buckling load capacity of conical tanks. As ovality increases, the onset of buckling occurs at lower applied loads, leading to premature structural failure. The presence of liquid filling further exacerbates the buckling phenomenon, with the liquid sloshing effect amplifying the structural response. The study also investigates the influence of different materials on the buckling behavior of conical tanks subjected to ovality. It is found that the material stiffness and yield strength play a crucial role in determining the critical buckling load and mode shape. Furthermore, the effect of liquid fill level is explored, demonstrating that higher fill levels increase the vulnerability to buckling.

Optimal pore shape in a low‐Pt PEM fuel cell cathode catalyst layer

AbstractA model for performance of an axially symmetric pore with the curved generatrix is developed. Oxygen transport along the pore axis and in the radial direction through a thin ionomer film separating the pore volume from the Pt/C surface is taken into account. A performance functional is formulated, and the Euler–Lagrange equation is solved numerically for an optimal pore shape. This shape is close to a cubic paraboloid converging toward the membrane. Polarization curves show superior performance of the optimal pore over the cylindrical pore of the same active (side) surface area. The results suggest the shape of optimal ionomer loading for low‐Pt electrodes.

Loading–shape interaction analysis of membrane structures subjected to deformation dependent hydrostatic loadings

Due to their flexibility, membrane structures loaded and/or supported by gas and/or fluid undergo large deformations when subjected to external loads, for example when a relatively flat membrane deflects under accumulative ponding. The most noteworthy feature during the deformation process is the loading–shape interaction since changes in the form of the structure induce changes in the loading profiles, and vice versa. Description of the hydrostatic loading is complex since the discontinuity of structural domain and fluid domain occurs with the deformation of membrane. In this paper, an interactive model dealing with accurate hydrostatic load description and nonlinear finite element analysis is employed to analysis the structural response. The hydrostatic loading is described in vectors by fluid level and loading direction in current mesh of the membrane. In case to conserve a specific volume, the free surface height is calculated with a Newton algorithm. Equivalent nodal forces evaluation on different elements are deduced especially when they are partially or fully loaded by judging the spatial relation between the element and the fluid domain, and integrating with shape functions and area coordinates in a local coordinate system. In case of multiple fluid domains, the hydrostatic load description procedure is proposed to be conducted for each fluid domain with care in identifying respective loading direction and then sum them up to get the total hydrostatic loading forces. Two numerical examples, (a) single fluid domain case: a flat membrane subjected to accumulative water loading, and (b) multiple fluid domains case: an air-inflated dam partially filled with water and loaded by lateral pressures of water, are presented to demonstrate correctness, performance and effectiveness of the proposed method in large displacement analysis of flexible membrane structures subjected to deformation dependent hydrostatic loading.

Energy absorbing 4D printed meta-sandwich structures: load cycles and shape recovery

The present study investigates the behavior of solid cellular structures in polylactic acid (PLA) achieved by FDM technology (fusion deposition modelling). The geometries are permanently deformed by compressive stress and then subjected to shape recovery through the application of a thermal stimulus. The structures are submitted to medium–high and medium–low compression stresses, evaluating the mechanical properties and the absorption energy as the number of cycles varies. The study shows that the ability to absorb energy is related to the density of the model, as well as the degree of damage observed, which increases with increasing number of load cycles. The strongest geometry is the lozenge grid, which is the most reliable. It shows no damage with increasing compression cycles and keeps its capability to absorb energy almost constant. The increase in lozenge grid density leads to an improvement in both mechanical strength and absorption energy, as well as a lower incidence of microcracks in the geometry itself due to the repeated load cycles. These results open up a broad spectrum of applications of custom-designed solid cellular structures in the field of energy absorption and damping.

Effects of Coarse Aggregate Rap Content on the Mechanical and Shear Performance of HMA by the UPT Method

Abstract In recent years, the use of materials derived from recycled asphalt has attracted the attention of airfield and highway construction researchers. Since the making of these products is economically cost-effective, one idea about how to use them is to use coarse-grained crumbs from recycled Asphalt Pavement (RAP), which are agglomerates that can be found in coarse RAP, as a replacement for virgin asphalt.The goal of the current study is to investigate the performance of hot mix asphalt created with various percents of RAP. The punching shear strength of cylindrical specimens versus the penetration of steel rods with fixed and determined diameters into an asphalt specimen is one of the tests used to study the shear strength of asphalt. Other typical tests include a test of the structural strength and resilient modulus with two rectangular and sinusoidal loading shapes, respectively, as well as the specimen's strength against different temperatures of asphalt mixtures containing 10, 20, and 30% coarse-grained RAP. The results show that the resilient strength of the samples with a maximum 30% coarse-grained RAP is within reasonable limits. Furthermore, the semi-sinusoidal loading has a higher resilience modulus than rectangular loading. It is also observed during uniaxial penetration testing (UPT) that increasing the RAP increases the penetration of the steel rod, thereby implying that the shear strength of the asphalt has decreased.

Wetland nitrogen removal from agricultural runoff in a changing climate

Wetlands in agricultural areas mitigate eutrophication by intercepting nutrient transports from land to sea. The role of wetlands for nutrient removal may become even more important in the future because of the expected increase in agricultural runoff due to climate change. Because denitrification is temperature dependent, wetland nitrogen (N) removal usually peaks during the warm summer. However, climate change scenarios for the northern temperate zone predict decreased summer and increased winter flows. Future wetlands may therefore shift towards lower hydraulic loading rate and N load during summer. We hypothesised that low summer N loads would decrease annual wetland N removal and tested this by examining 1.5–3 years of continuous N removal data from created agricultural wetlands in two regions in southern Sweden (East and West) during different periods. West wetlands showed relatively stable hydraulic loads throughout the year, whereas East wetlands had pronounced no-flow periods during summer. We compared East and West wetlands and tested the effects of several variables (e.g., N concentration, N load, hydraulic load, depth, vegetation cover, hydraulic shape) on annual absolute and relative N removal. We found no difference in annual N removal between East and West wetlands, even though summer N loads were lower in East than in West wetlands. A possible explanation is that stagnant water conditions in East wetlands suppressed decomposition of organic matter during summer, making more organic matter available for denitrification during winter. Absolute N removal in all wetlands was best explained by N load and hydraulic shape, whereas relative N removal was best explained by emergent vegetation cover and hydraulic shape. This study highlights the importance of design and location of agricultural wetlands for high N removal, and we conclude that wetlands in a future climate may remove N from agricultural runoff as efficiently as today.