Comparative Performance Assessment Research Articles

Techno-Economic Comparative Assessment of High Temperature Heat Pump Architectures for Industrial Pumped Thermal Energy Storage

Abstract The industrial sector is a key global source of wealth, but it is also recognized as a major challenge toward worldwide decarbonization. Today the industrial sector requires more than 22 % of the global energy demand as thermal energy and produces for this about 40 % of the total CO2 emissions. Solutions to efficiently decarbonize the industrial sector are deemed. This work presents a comparative techno-economic performance assessment of a high temperature heat pump integration within a molten salts based power to heat system for industrial heat flexible generation. The main system performance is reported in terms of required working conditions and temperature for the heat pump and thermal demand size as well as reduction of the attainable levelized cost of heat (LCoH) against non-flexible electric boiler based systems. The impact of different industrial load profiles, electricity prices, heat pump capital cost and heat pump real to Carnot efficiency ratio are also presented. The results highlight that the proposed system can be cost-competitive, particularly for thermal demand around 10 MW and waste heat temperatures above 80°C. Under these conditions LCoH reductions higher than 15 %, with respect to the considered non-flexible electric boiler alternative, are attainable. These LCoH reductions are primarily driven by savings in electrical consumption as high as 30 %. This study sets the ground for further power-to-heat techno-economic investigations addressing different industrial sectors and identifies main system and components design strategies, integrations, and targets.

Influence of green solvents on the recovery of cathode active materials from electrode scraps: A comparative study

Direct recycling of cathode materials from spent Li-ion batteries (LIBs) or electrode scraps necessitates the efficient recovery of active materials from the aluminum foil. The variability in electrode types and recovery processes across previous studies complicates the comparative assessment of the recovery performance of green solvents. In this study, we evaluated the performance of three green solvents—triethyl phosphate (TEP), dihydrolevoglucosenone (Cyrene), and propylene carbonate (PC)—in recovering valuable active materials from industrial-grade cathode scraps. Using ultrasonication, we developed a standardized, energy-efficient recovery process that eliminated the need for conventional stirring and achieved complete cathode delamination from the aluminum foil. Furthermore, we successfully recovered the used green solvents after the process, ensuring their reuse and supporting a circular economy. The recovered materials retained their original morphology, chemical composition, and crystalline structure; however, the presence of surface impurities varied significantly depending on the green solvent used. These impurities had a considerable impact on the electrochemical performance of the recovered materials. TEP and PC yielded high-purity active materials and aluminum foils suitable for reuse or direct recycling, while Cyrene resulted in substantial residues of PVDF/solvent, requiring additional post-processing. Additionally, the recyclability of these green solvents was influenced by their solubility power for PVDF. This study provides valuable insights into the green solvent-based recycling process, laying the groundwork for future sustainable practices in LIB recycling.

Beyond the Finish Line: Muscle Injuries in Athletic Competition

Objectives. The study aimed to compare the incidence of muscle injuries in the qualifying rounds, semifinals and finals in athletics. Materials and Methods. A total of 14 male and 12 female athletes who participated in all rounds (preliminaries, semifinals, and finals) of the 100 m, 200 m, and 400 m matches were analyzed over a 4-year period starting in 2021-2024. The female athletes were aged 22.4 ± 3.81 years, with a mean height of 167 ± 8.6 cm, and weight — 64.6 ± 17.5 kg. The male athletes were aged 23.4 ± 3.82, having an average height of 169 ± 8.3 cm, and weight — 66.4 ± 15.8 kg. A t-test was used to conduct comparative assessment of performance between finals, semifinals, and preliminaries for each gender and event. A 95% confidence interval was calculated separately for each gender, event, and round. Additionally, incidence rates were compared. The significance level was accepted at p < 0.05. Results. HMI (hamstring muscle injuries) incidence rate for female qualifiers was found to be 1.50 (1.05-1.95), semifinals — 1.33 (0.79-1.88), and the final — 1.91 (1.44-2.38). LLMI (lower limb muscle injuries) incidence rate among female qualifiers was 1.50 (0.58-2.42), semifinals — 1.00 (1.00-1.00), and the final — 1.55 (1.36-1.74). HMI incidence rate in male qualifiers was 0.50 (0.08-1.28), semifinals — 0.67 (0.77-2.10), and 1.00 (0.34-1.66) in the final. LLMI incidence rate for male qualifiers was 0.40 (0.28-1.08), semifinals — 0.24 (0.55-1.05), and the final revealed 0.60 (0.08-1.28). Conclusions. The highest incidence of muscle injury in all forms among men was observed in the all-round category. In women, hamstring muscle injuries occurred in the final, while lower limb muscle injuries were most prevalent in the preliminaries and semifinals.

A comparative performance assessment of artificial intelligence based classifiers and optimized feature reduction technique for breast cancer diagnosis

Breast cancer (BC) is a catastrophic global health concern that causes numerous fatalities worldwide. Early detection of breast cancer may mitigate death rates; however, the prevailing diagnostic procedure for the malignancy necessitates numerous multifaceted laboratory tests that must be performed by medical professionals. In this article machine learning, a branch of Artificial Intelligence (AI), has been employed to improve cancer diagnosis, prognoses and survival rates while reducing the vulnerability of humans. Support Vector Machine (SVM), K-nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF) and Grey Wolf Optimizer (GWO) are implemented to prognosticate breast cancer. Comprehensive insights into the efficacy of these approaches for breast cancer prognosis are provided by the performance assessment that is accomplished using the confusion matrix, Receiver Operating Characteristic (ROC) curves and parallel coordinate plots. Both UCI (University of California Irvine) and SEER (Surveillance, Epidemiology and End Results) datasets have been utilized to confirm the investigation's findings and ensure their generalizability across diverse data sources. The results conclusively demonstrate that SVM is the cohort's most accurate classifier. With a stupendous accuracy rate of 99.1 %, the GWO-SVM compares favorably to all other algorithms. Furthermore, feature reduction approaches such as Minimum Redundancy Maximum Relevance (mRMR), ReliefF and Principal Component Analysis (PCA) are utilized. ReliefF has demonstrated exceptional effectiveness with a maximum accuracy of 98.2 %.

Integration of Moving Bed Biofilm Reactor (MBBR) and algal PhotoBioReactors (aPBR) for achieving carbon neutrality in wastewater treatment

Carbon neutrality is a primary goal for wastewater treatment plants (WWTPs), as they are responsible for significant greenhouse gas (GHG) emissions as well as unpleasant odour emissions.The paper shows a new modular biotechnology that enables simultaneous treatment of gaseous emissions and biofixation of CO2.A comparative assessment of system performances in removing target pollutants (toluene, p-xylene and hydrogen sulphide) was implemented. Results showed that the highest removal efficiency (RE) was recorded for the toluene, equaling 99.9 ± 0.1 %, for an inlet load (IL) of 9.91 ± 3.44 g m−3 d−1. During the experimental tests regarding hydrogen sulphide removal, the system recorded the highest CO2 assimilation, equal to −3.03 ± 0.93 g m−3 d−1. However, this assimilation rate did not correspond to the maximum volumetric biomass productivity (MVBP), equal to 1.3 g L−1 d−1, recorded with toluene treatment, with a maximum lipid productivity (MLP) of 450 mg L−1 d−1.The results demonstrated the complete adaptability of the investigated system, which can help to fill the gaps in the current technological landscape, providing an innovative biotechnology that can be directly implemented and environmentally sustainable.

Comparative performance assessment of different halide composites in sorption cooling system: A dynamic approach

The adsorption technique presents a promising approach for cooling, heat storage, and gas storage. This study focuses on the viability of adsorption in cooling applications, specifically utilizing various halide salts in conjunction with thermal energy, highlighting its potential as an energy-efficient solution for modern energy demands. A dynamic numerical model is developed and used to study the performance of transverse finned reactor-based adsorption cooling system (ACS) with different halide composite salts. The simulations are carried out at different supply pressures ranging from 3.55 bar to 7.28 bar corresponding to saturation pressure of ammonia at an evaporator temperature ranging from −5 ℃ to 15 ℃ during adsorption. The desorption process is simulated at different regeneration temperatures with a required desorption pressure of 17.28 bar corresponding to saturation pressure at condenser operating temperature of 40 ℃. The average cooling power produced in first 60 min of system operation at an evaporator temperature of −5 ℃ is 4.89 W, 207 W, 206 W and 925 W with the use of BaCl2, CaCl2, SrCl2 and MnCl2 composites respectively. The theoretical maximum coefficient of performance (COP) obtained are 0.31, 0.365, 0.308 and 0.552 with BaCl2, CaCl2, MnCl2 and SrCl2 respectively. The cooling power (CP) is increasing with increase in evaporator temperature. The shortest adsorption completion time is observed at 15 ℃ of evaporator temperature with all metal halides used. The lowest adsorption time is observed with MnCl2 composite salt and highest with BaCl2 composite salt. The regeneration time of all composite salt beds is decreasing with increase in regeneration temperature.

Comparative Performance Assessment between Incompressible and Compressible Solvers to Simulate a Cavitating Wake

To study the effects of fluid compressibility on the dynamics of a cavitating vortex street flow in a regime where the vortex shedding frequency increases as a result of the cavitation increase, the cavitating wake behind a wedge was simulated employing both incompressible and compressible solvers. To do this, a compressible cavitation model was implemented, modifying the Zwart-Gerber-Belamri (ZGB) incompressible solver and including a pressure limit and absorbing boundary conditions to prevent a non-physical pressure field. To validate the performance of the compressible model, preliminary simulations were carried out on a 1D Sod cavitating tube and the cavitating vortex shedding behind a circular body at laminar flow conditions. The results of the cavitating wake behind the wedge with the incompressible and the compressible solvers showed similar predictions in terms of pressure, vortex shedding frequency, and instantaneous and average vapor volume fraction profiles. In spite of this, differences were obtained in the energy content of the fluid force fluctuations on the body at higher frequencies, which appear to be better resolved and amplified when the compressibility model is considered. Overall, both solvers provided comparable results in terms of cavitation phenomena that are well aligned with experimental observations.

The application of direct ridership models in the evaluation of the expansion of the Porto Light Rail Transit

The main purpose of this paper is to show how a direct demand ride model coupled with a transfer model was able to support the choice of alternative routes for the expansion of the light rail system serving the Porto Metropolitan Area. After an overview of the literature on direct ridership models, emphasizing some key issues such as the need for a systematic assessment of their forecasting performance, the issues related to the definition of the pedestrian catchment area and the limitations of the simultaneous consideration of demand and supply effects, the paper moves into the case study, providing some background information on current occupation densities, land uses and mobility patterns, as well as on the performance of the existing LRT in the Metropolitan Area of Porto. The development of the direct ridership model, measuring the potential attractiveness of each station, and the transfer model, measuring the number of transfers at each station, are presented in detail. A justification is provided why, in this case, a two-step modelling approach was necessary. Further details about the statistical tests for model validation are also provided. After a brief characterization of the alternative routes under analysis for the expansion of the network, the modelling results are presented enabling a comparative assessment of the potential performance of each proposed route. The paper ends with a discussion of the relevance of this modelling results vis a vis the actual final decisions on investment priorities taken jointly by the Metropolitan Council and the Metro Company.

Empirical analysis of 5G deployments: A comparative assessment of network performance with 4G

The advent of 5G networks has introduced new challenges for network operators, particularly in terms of coverage, capacity, and service quality. Consequently, it is crucial to monitor and assess network performance to detect irregularities and enhance functionality and deployment efficiency. This is especially important for Non-Standalone (NSA) 5G networks, which rely on existing 4G infrastructure and may not fully utilize the advanced capabilities of 5G technology. This study evaluates wireless system/network performance, focusing on key quality indicators and data throughput within typical town settings featuring various operational scenarios. To achieve this, portable smartphone devices were employed to simultaneously measure real-world data from all 5G and 4G networks, providing a comparative analysis across all (three) cellular network providers in the area.Results highlight differing 5G rollout strategies and performance across operators, revealing that broad coverage may struggle with congestion issues, while a tailored deployment approach could yield better results. Additionally, the analysis pinpoints performance challenges related to coverage, throughput, resource utilization, and interference, thus guiding enhancements in 5G network deployments and establishing a baseline for tracking the evolution of 5G performance.

Comparative Assessment of Water Productivity and Crop Performance of Cluster Bean, Cowpea and Pearl Millet in Arid Zones

Arid and semi-arid regions face mounting challenges due to water scarcity exacerbated by climate change, necessitating sustainable agricultural practices to ensure food security and economic stability. This study compares the water productivity and crop performance of Cluster Bean (Cyamopsis tetragonoloba L), Cowpea (Vigna unguiculata L.) and Pearl Millet (Pennisetum glaucum L.) under sprinkle irrigation in the Thar Desert, India. The experiment, conducted over two years (2022 and 2023) at ICAR – CSWRI – Arid Region Campus, Bikaner evaluated plant height, leaf number, branch development, fresh and dry biomass yields and water productivity. Pearl Millet exhibited the tallest plants (160.03 cm) and highest water productivity (1.57 kg/m³), emphasizing its drought resilience and efficient water use. Cowpea demonstrated substantial biomass production (average fresh weight of 16,348.75 kg/hac.) and moderate water productivity (1.16 kg/m³), suitable for forage and soil improvement. Cluster Bean, although less productive in biomass, showed adaptability with increased branching (from 4.65 to 7.35 branches/tiller/plant), indicative of its resilience in arid conditions. These findings underscore the importance of crop selection and management practices in maximizing agricultural productivity and resource use efficiency in water-limited environments.

Comparative assessment of the diagnostic performances of particle-based multianalyte technology and commercial ELISA for antiphospholipid autoantibody testing

Background: Diagnosing Antiphospholipid Syndrome (APS) relies heavily on laboratory findings, particularly the detection of specific antibodies like lupus anticoagulant (LA), IgG and/or IgM anti-cardiolipin (aCL), and IgG and/or IgM anti-β2 glycoprotein 1 (aB2GP1). Although ELISA is widely used in the US for this purpose, standardization between different assay methodologies remains challenging, leading to significant variability across laboratories. Particle-based multi-analyte technology (PMAT) offers a streamlined one-step detection for all six antiphospholipid (aPL) autoantibodies, covering aCL and aB2GP1 of IgA, IgG, and IgM isotypes. Methods: In this study involving 224 subjects, including 34 clinically diagnosed with APS, alongside 160 non-APS patients and 30 healthy donors, PMAT’s performance was evaluated against commercial ELISA in detecting aPL antibodies. Results: At the manufacturer’s suggested cutoff, PMAT exhibited sensitivity comparable to ELISA, albeit with a low to moderate decrease in specificity for certain antibodies. With anti-CL IgM alone, PMAT displayed a 17.7% decrease in sensitivity, accompanied by a corresponding 31.1% increase in specificity compared to ELISA. However, applying a stricter cutoff (88–90% specificity), IgA and IgM antibodies yielded 5.9–17.6% higher sensitivities with PMAT, and IgG antibodies displayed similar sensitivity. Conclusions: In this study cohort, PMAT demonstrated higher or comparable sensitivity to that of commercial ELISA for all six aPL antibodies at a specificity cutoff near 90%. Notably, PMAT demonstrated superior sensitivity and specificity overall in detecting IgA aCL and aB2GP1 antibodies. This study highlights the potential of automated PMAT for detecting aPL antibodies in APS evaluation.

A Comparative Performance Assessment of the Integrated Upflow and Surface Flow-Based Constructed Wetlands Dosed with Landfill Leachate: Electrode Coupling and Input Load Variation

This study reports organic, nutrient, and coliform removal performances of two integrated wetlands designed to treat landfill leachate. Each integrated system included two components: a normal or electrode-integrated upflow-based wetland and a surface flow wetland (with internal baffle walls). The components were fully or partially filled with stone dust media and planted with Canna indica. Two hydraulic loading rates, i.e., 15 L and 60 L (per day), were applied. The integrated wetlands achieved a mean biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and coliform removal efficiency ranges of 89–94%, 95–97%, 85–91%, 91–98%, and 70–88%, respectively, within the applied loading ranges. The electrode-dependent system achieved better pollutant removal performances due to the influence of electrochemical-based bioreactions that fostered microbial decomposition. Nitrogen accumulation percentage (with respect to observed removal) in plant tissues ranged between 0.6 and 25%; phosphorus accumulation percentage was negligible, i.e., ≤0.009%. The chemical composition of the stone dust media supported nutrient adsorption. Stable nutrient removal performance was observed with both systems despite variable loading ranges due to pollutant removal in the upflow-based wetlands followed by controlled flow direction (induced by baffle walls) in the surface flow wetlands that triggered chemical and biological removals. Mean power density production ranged between 235 and 946 mW/m3 with the electrode-based integrated wetland system. In summary, this study demonstrates the application of integrated wetland systems to treat landfill leachate and the associated factors to achieve stable removal under variable loading ranges.

Experimental response characterization and comparative seismic performance assessment of a long-stroke shape memory alloy bridge restrainer

In this study, a long-stroke SMA Restrainer (LSR) device was fabricated and its response was characterized through experimental testing. The LSR consists of a long SMA bar encased in a steel tube to prevent its buckling. First, an optimal heat treatment procedure was identified to obtain superelastic response for SMA bars. Subsequently, the LSR underwent testing using an increasing amplitude tension-compression loading protocol and its mechanical properties such as equivalent stiffness and equivalent viscous damping ratio were computed. Based on the experimental findings, a high-fidelity 3D finite element model of LSRs was developed, which then used to design a full-scale LSR and verify its performance. Nonlinear time history analyses were conducted to assess the seismic performance of the proposed restrainers when used in a four-span simply supported bridge structure. The response of a case-study bridge equipped with steel cable restrainers, SMA bar restrainers, or LSRs were comparatively evaluated using a set of 40 near-fault ground motion records. Both SMA bar restrainers and LSRs were able to effectively limit the displacement response and provide the re-centering capabilities, while LSRs producing similar moments on piers compared to steel cable restrainers. In addition, compared to tension-only SMA bar restrainers, the LSRs require about only a quarter of SMA materials used in SMA bar restrainers.

Comparative assessment of growth performance, heat resistance and carcass traits in four poultry genotypes reared in hot-humid tropical environment.

This study investigated the impact of heat stress on growth and carcass traits in four poultry genotypes-Giriraja, Country chicken, Naked Neck and Kadaknath reared in a hot and humid tropical environment. Birds from all genotypes had ad libitum access to feed and water while being challenged with consistently high environmental temperatures in the experimental shed. Daily diurnal meteorological data were recorded inside and outside the shed. The study specifically examined growth variables and carcass characteristics. Significant differences (p < 0.01) were observed in body weight and average daily gain at various intervals. Notably, feed intake showed significant differences (p < 0.01) across weeks, indicating interactions between genotypes and time intervals. The feed conversion ratio (FCR) varied significantly (p < 0.01), with the highest FCR recorded in the Kadaknath breed. Livability percentages were similar across groups, except for Giriraja, which had significantly lower livability (p < 0.01). Carcass traits, including dressing, wings, feathers and giblet percentages, showed significant differences among genotypes (p < 0.01). Hepatic mRNA expression of growth-related genes revealed numerical variations, with Naked Neck displaying the highest (p < 0.05) fold change in IGF-1 expression compared to other genotypes. The study recognized in the Naked Neck genotype to possess higher resilience in maintaining homoeostasis and uncompromised growth under heat stress, providing valuable insights for sustainable poultry farming in challenging environmental conditions.

Comparative assessment of psychometric performance on the adjusting amounts versus the 21-item Monetary Choice Delay Discounting tasks among young adult substance users.

Delay discounting (DD) assessments offer a wide variety of procedures to suit specific clinical and research needs. This study compared the reliability and validity of two DD tasks: (a) an adjusting amounts task presented on a computer (AAC) and (b) the 21-item Monetary Choice Task, which was administered online (MCT). Participants were 1,573 Spanish young-adults reporting past-month substance use. Measures included quantity and severity of drug use (i.e., cigarette smoking, cannabis, alcohol) and two DD assessments (i.e., AAC, MCT). Reliability was assessed using both the classical test and item response theory. Correlations and linear regressions examined the validity of both DD tasks in relation to substance use. The MCT showed higher internal consistency than the AAC (α = .941 vs. α = .748). AAC precision was adequate for moderate levels of discounting (θ values between -2 and +2), but the MCT showed superior reliability at low, moderate, and high levels of discounting (θ values between -1 and +1.5). Both DD tasks showed more significant correlations for alcohol-related measures (|rs| ranged between .053 and .093) compared to cigarettes and cannabis. The incremental validity of DD tasks in relation to nicotine dependence (AUClogd: β = -.664, 95% CI [-1.256, -.071]) and alcohol problems (AUClogd: β = -3.098, 95% CI [-5.209, -.988]) was only supported for the AAC. The MCT was more reliable than the AAC for measuring impulsive choice in young adult substance users. Nevertheless, the AAC may serve as a valid marker of nicotine dependence and alcohol problems. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Comparative Performance Assessment of RCS Connections Across Different Generations of ASCE Guidelines

Comparative Performance Assessment of RCS Connections Across Different Generations of ASCE Guidelines

Comparative assessment of emissions, performance, and economics parameters for a dual–fuel diesel generator operating with rice bran biodiesel and hydrogen

The first step to achieving an energy transition is partially substituting fossil fuels with other more environmentally friendly alternatives, such as hydrogen gas. The current research aims to evaluate the influence of hydrogen in a diesel generator fueled with rice bran biodiesel. The above encourages the use of hydrogen and biodiesel production from residual raw material. For the development of the research, a diesel engine bench was used, which operated in five load conditions: 20 %, 40 %, 60 %, 80 %, and 100 %, and was fed with three fuels: −100 %, RB-10 %, and RB-10 % + H2(30 %). The results show that the mixture RB-10 % + H2(30 %) causes a 3.14 % reduction in BSFC and a 3.26 % increase in energy conversion efficiency. In addition, it is observed that a 9.90 %, 12.57 %, and 10.99 % decrease in HC, CO, and smoke opacity emissions compared to pure diesel. On the other hand, the mixture RB-10 % + H2(30 %) reduces by 4.44 %, 5.07 %, and 7.06 % the environmental, social, and ecological impact due to CO2, HC, and CO emissions, as well as a 3.93 % reduction in engine operating cost compared to RB-10 % biodiesel. In general, hydrogen injection is a promising alternative to promote the use of rice bran biodiesel due to its increased performance characteristics and reduced pollutant emissions without the need to modify the engine.

Governing accelerating Universe via newly reconstructed Hubble parameter by employing empirical data simulations

A new parametrization of the Hubble parameter is proposed to explore the issue of the cosmological landscape. The constraints on model parameters are derived through the Markov Chain Monte Carlo (MCMC) method by employing a comprehensive union of datasets such as 34 data points from cosmic chronometers (CC), 42 points from baryonic acoustic oscillations (BAO), a recently updated set of 1701 Pantheon+ (P22) data points derived from Type Ia supernovae (SNeIa), and 162 data points from gamma-ray bursts (GRBs). Furthermore, the models are compared by using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), so that a comparative assessment of model performance can be available. Additionally, we compare the Dainotti relation via Gaussian likelihood analysis versus new likelihoods and Calibration of the Dainotti relation through a model-independent method. The kinematic behavior of the models is also investigated by encompassing the transition from deceleration to acceleration and the evolution of the jerk parameter. From the analysis of the parametric models, it is strongly indicated that the Universe is currently undergoing an accelerated phase with diagnostics of the model validating the quintessence phase.

Comparative performance assessment of pilot irrigation schemes in Uganda

Irrigation schemes across sub-Saharan Africa are constructed with the intention of increasing agricultural production to increase food security, reduce poverty and improve economic growth. However, most of these schemes are not performing as expected. This study therefore, diagnosed performance gaps in the pilot irrigation schemes of Mubuku and Doho in Uganda and analysed sustainable improvement options. Data was collected through systematic review of literature and scheme data, direct measurements at the schemes, field surveys, inspections, and key informant interviews. For each scheme, data for climate, irrigation, flow measurements, crop yields and farm gate prices were collected. Comparative indicators of agricultural output, water supply, financial and physical sustainability were used to assess scheme performance using standard approaches by International Water Management Institute (IWMI). The findings showed that the schemes were not performing optimally with crop yields being far below the attainable potential. The major contributing factors to the low performance were low water use efficiency and low agricultural output. Poor flow control, poor water distribution, and poor on-farm water application contributed to low water use efficiency. Low agricultural production was attributed to poor crop yields resulting from poor agronomic practices, poor irrigation scheduling and low produce prices. The financial self-sufficiency indicator pointed to farmers’ inability to operate and maintain irrigation schemes effectively. Improving the irrigation schemes performance requires a multidisciplinary approach targeting the improvement water use efficiency and agricultural output.

Comparative seismic performance evaluation of friction, self-centering and hybrid self-centering dampers

This study explores comparative seismic performance of a shape memory alloy (SMA)-only device, a friction damper, and a hybrid self-centering device. The self-centering device considered in this study, named as superelastic friction dampers (SFDs), is a hybrid damper operating on a mechanism where SMA cables and frictional components are arranged in parallel. A detailed description of the device and an experimental characterization of mechanical behavior are presented first. Then, an 8-story archetype steel frame building is designed and modeled with each seismic protection device (SMA-only, hybrid self-centering, and friction only). To enable comparative performance assessment, each device is designed to have similar initial stiffness and the same maximum force at design displacement. Nonlinear time history analyses are conducted using a total of 44 ground motion records. The results are evaluated to compare performance of each frame design at design-basis and maximum considered earthquake hazard levels. Next, a risk-based seismic hazard demand analysis framework that involves comprehensive incremental dynamic analyses is employed for further assessing the performance of each system. The experimental results validate the parallel working mechanism of SMA cables and frictional components in the SFD, with 90% of the damper deformations recovered. Comparative analysis of seismic responses demonstrates the excellent performance of the SFDs in reducing interstory drift ratio, residual interstory drift ratio, and absolute acceleration responses. Furthermore, fragility analysis and risk-based seismic hazard assessment further reveal that the SFDs provide a well-balanced combination of energy dissipation capability and self-centering ability, thereby enhancing the seismic resilience of structures.