Short-term voltage stability assessment (STVSA) plays a critical role in ensuring the stable operation of power systems, yet it suffers from excessive time consumption and computational burdens. While existing data-driven approaches accelerate the assessment by replacing time-domain simulations, this letter proposes a proactive search method of critical operating point (OP) in extensive OP space to further enhance the efficiency of batch STVSA. First, by predicting the voltage stability index through a convolutional neural network (CNN) to proactively identify critical OPs, the assessment focuses on the OPs with the lowest stability margins. Then, leveraging Shapley additive explanations (SHAP) analysis, substantial OPs with elevated instability severity are proactively searched for targeted assessments. This methodology effectively enhances the efficiency of STVSA by eliminating redundant assessments of evidently stable OPs. Case studies on a realistic 10,000-bus test system in the China Southern Power Grid validate the accuracy and efficiency of the proposed approach.

Nonlinear ultrasonic testing (NLUT) techniques have been extensively investigated for their potential to assess damage states and monitor damage evolution. Among these, the Scaling Subtraction Method (SSM) offers a state-of-the-art approach by capturing the strain-dependent nonlinear behaviour of the testing material under low- and high-voltage excitations. This study extends the application of SSM by enabling continuous monitoring and rigorously quantifying intrinsic system nonlinearity. The influence of excitation waveform, excitation frequency and excitation voltage on the nonlinearity indicator was also examined. A series of experiments were performed to isolate nonlinear contributions from waveform generators, power amplifiers, transducers and the material of interest. Results demonstrate that the proposed testing parameters and testing system result in a negligible nonlinearity compared to the substantial nonlinearity measured in an alternative nonlinear testing system and in marble. Continuous ultrasonic excitation over 900 s, conducted in the absence of external mechanical loading, revealed a time-dependent increase in the nonlinearity indicator for marble specimens, while the ultrasonic system itself remained stable throughout the prolonged excitation. These findings highlight the importance of quantifying intrinsic system nonlinearity and optimising excitation parameters for accurate nonlinearity evaluation. Continuous SSM monitoring of marble during uniaxial loading demonstrated the method's high sensitivity and resolution, clearly capturing progressive changes in nonlinearity with increasing stress. Taken together, these results establish SSM as a robust and practical tool for real-time monitoring of damage evolution in rock-like materials.

Timber chocks are commonly used in underground operations as the standing support system to stabilise the excavations. They are constructed by stacking notched hardwood components into interlocking structures, and depending on various factors such as level of stress redistribution, ground movement, and roof or floor convergence, they could be subjected to different actions including combined vertical and horizontal. This study, for the first time, examines the mechanical performance of timber chock under combined actions, being (1) axial service load followed by ultimate axial displacement to failure; (2) axial service load followed by ultimate lateral displacement to failure and (3) axial service load followed by a combination of ultimate axial and lateral displacements simultaneously to failure. Nine timber chock specimens are tested using the Multi-Axis Substructure Testing (MAST) system followed by an extensive experimental analysis. These include the performance of specimens from the elastic range through to collapse along with the damage progression analysis, offering critical insights into the load carrying capacity, damage initiation and failure mechanisms of timber chock under complex loading conditions envisaged in the underground mining environments. • Characterising the mechanical behaviour of timber support system under axial, lateral and combined actions. • Assessing the damage progression and failure mechanisms of timber support system under complex loading conditions. • Development of a design protocol to enhance the performance and safety of timber support system in service.

Test case specification techniques and system testing tools in the automotive industry: A review

Out-of-plane waviness (ply wrinkles) reduces tensile and compressive strength in Carbon Fibre Reinforced Polymers (CFRPs), with maximum out-of-plane ply angle governing failure mechanisms. This study comparatively evaluates three Non-Destructive Evaluation (NDE) techniques: Eddy Current Array Testing (ECAT), Phased Array Ultrasonic Testing (PAUT) and X-ray Digital Tomosynthesis (DT) for detecting and characterising ply wrinkles across three parameters: amplitude, wavelength, and maximum out-of-plane ply angle. Nine unidirectional CFRP coupons containing induced ply wrinkles of controlled amplitudes (0.13 -1.31 mm) were inspected, addressing a critical gap in comparative NDE performance for sub-2 mm amplitude defects in thin laminates. PAUT achieved the highest overall characterisation success rate of 96.3% (26/27 measurements) and a detection success rate of 88.9% (8/9 samples). Critically, PAUT achieved 100% success in characterising maximum out-of-plane ply angle - the parameter governing compressive/tensile failure across all samples, including the lowest amplitude wrinkle (0.13 mm). However, systematic overestimation in wrinkle amplitude characterisation occurred (+55.3% mean percentage error). ECAT achieved an equivalent 88.9% detection success and 33.3% characterisation success, successfully measuring wrinkle wavelength (100%) but unable to quantify wrinkle amplitude or out-of-plane ply angle from complex impedance data alone, positioning it as a rapid automated screening tool. X-ray DT achieved 88.9% detection and characterisation success, with moderate overestimation in wrinkle amplitude characterisation (+24.8%). However, complete detection and characterisation failure occurred on the lowest amplitude ply wrinkle. A critical finding establishes that reliable characterisation requires ply wrinkle amplitudes ≥0.32 mm across all techniques, with implications for the wrinkle parameter hierarchy in manufacturing quality control. • Implementation of a robotically deployed Eddy Current Array Testing (ECAT) system to automate the inspection of the Carbon-Fibre Reinforced Plastic (CFRP) laminates affected by out-of-plane ply wrinkles. • Implementation and investigation of X-ray Digital Tomosynthesis (DT) as an emerging technology for rapid inspection of out-of-plane ply wrinkles in CFRP laminates. • A comprehensive tri-modal comparative evaluation of ECAT, Phased Array Ultrasonic Testing (PAUT), and X-ray DT for detecting and characterising out-of-plane ply wrinkles with amplitudes below 2 mm in thin CFRP laminates based on ply wrinkle parameter hierarchy (Maximum out-of-plane ply angle, amplitude and wavelength).

This paper describes the design, construction, and test results of the conduction cooling-type HTS module testing system. The constructed conduction cooling-type HTS module testing system uses two two-stage GM cryo-coolers as the primary cooling source. The 1st stage cold head of the cryo-cooler is responsible for cooling the metal current leads and radiation shields, and the bottom side of the HTS leads. The 2nd stage temperature section is responsible for cooling the Oxygen Free Copper (OFCu) cooling plate and top-side of the HTS leads. The HTS test module is cooled through the OFCu cooling plate. The HTS module testing system controls the temperature of the HTS module under testing from 4 K to 30 K and can supply an operating current of up to 800 A. All operating parameters of the HTS module test system are controlled and recorded using a Data Acquisition (DAQ) system based on LabVIEW.

Electric Vehicle Charging Stations (EVCS), Distributed Static Compensators (DSTATCOM), Battery Energy Storage Systems (BESS), and Distributed Generators (DGs) are integrated and operate in a coordinated way into radial distribution systems (RDS) to offer substantial aids in terms of voltage support, loss minimization, and reliability enhancement during regular operation. However, the decision to take their placement optimally and simultaneously is a complex task due to the nonlinear, bidirectional, and highly constrained nature of the radial distribution system. In response to this issue, this paper proposes an enhanced fractional order differential evolution (EFODE) for a more accurate, reliable, and optimal solution. Unlike non-adaptive versions of differential evolution (DE), which have insufficient exploration ability and lack adaptability to historical information, this study proposes an innovative approach to fractional-order DE (FODE). The proposed strategic formulation impact on enhancing DE performance. A bi-strategy co-deployment framework is incorporated, combining the concepts of population-based and parameter-based strategies to leverage their respective individual advantages, nullifying their limitations through mutual influence. In addition, the fractional order (FO) calculus is used to enhance the differential vector’s exploration and exploitation abilities, which are achieved through the incorporation of historical information from populations in the formulation, thereby ensuring the diversity of populations in an evolutionary process. By adaptively varying the most sensitive system factors dynamically according to the system’s performance, it accelerates convergence and prevents premature stagnation. The proposed method is simulated and validated on standard IEEE RDS 33, 69 and 85 test systems, considering multiple constant load, voltage-dependent variable load, and penetration scenarios. Simulation and comparative results demonstrate significant improvements in terms of voltage profile, reduction of active power loss, and overall solution quality. The comparative analysis with conventional metaheuristics confirms the effectiveness and robustness of the approach.

Context and objective: To facilitate sustained productivity gains in wheat and maize across Europe, we analysed a long-term (2003–2018) European Value for Cultivation and Use (VCU) dataset to quantify genotypic (G) and genotype-by-environment interaction (GEI) variation and to assess variety-testing precision for grain yield. Methods: Mixed-model analyses were applied to partition genetic and environmental sources of yield variation across European VCU networks in seven countries and to estimate variety-comparison precision (LSDs) and annual genetic trends for both crops. Results: Across Europe, G and GEI variances were comparable, explaining in total 10–29 % of total phenotypic variance in wheat and 8–29 % in maize. LSDs ranged 0.29–0.56 t ha⁻¹ and 0.38–0.81 t ha⁻¹, respectively. Genetic trends ranged 0.45–1.81 % yr⁻¹ for wheat and 0.90–1.31 % yr⁻¹ for maize. Testing precision allowed effective comparison of wheat and maize varieties differing by 2.7–10.5 and 3.3–6.4 release years, respectively, aligning with typical breeding turnover rates. Stronger GEI was associated with larger genetic trends in maize yield, whereas in wheat, observed trends were substantially smaller than the maximum potential implied by GEI magnitudes. Combining data from national VCU networks improved precision and allowed for efficient comparison of varieties not jointly tested. Conclusions: European VCU networks are well-optimized for the number of testing locations given national evaluation periods (2–3 years). Strengthening connections among national VCU networks could further improve precision, while integrating environmental and genetic information would enable a predictive testing system, accelerating breeding progress and the development of resilient varieties. Significance: This first pan-European appraisal of current VCU testing efficiency for two major crops provides a quantitative basis for optimizing variety evaluation across Europe.

Investigation of heat-induced oat drink fouling: Design and validation of a technical-scale test system

• A novel hybrid optimization approach for the optimal allocation and sizing of synchronous condensers (SynCons) in weak grids, addressing the challenges posed by large search spaces. • The methodology combines analytical and metaheuristic techniques and adapts automatically to the system under study, eliminating the need for manual candidate selection. • Case study results show that it significantly outperforms conventional metaheuristic-based optimization techniques, the current standard in the SynCon sizing and placement problem. • It can be easily integrated into planning workflows used by TSOs and consultants in long-term grid development studies. In power systems with high inverter-based resource penetration, synchronous condensers (SynCons) have become a widely deployed solution to ensure minimum grid strength levels. The optimal sizing and placement of SynCons is a complex task, particularly in large power systems. As the number of candidate buses for the installation of SynCons increases, the search space grows exponentially, leading to high computational costs and reduced effectiveness of conventional optimization techniques. To address this issue, this paper proposes an enhanced optimization methodology based on adaptive search-space reduction. The approach combines two complementary strategies: (i) the preselection of the most impactful candidate buses for grid strength enhancement using a novel metric, the Strength Sensitivity Index, and (ii) an iterative pruning process that filters out low-impact buses based on their historical allocation in previous optimization iterations. These techniques reduce the dimensionality of the problem while preserving solution quality. Simulation results on a modified IEEE 39-bus test system demonstrate that the proposed methodology accelerates convergence and improves the reliability of identifying optimal solutions, making them well-suited for long-term planning of weak grids.

This paper proposes a customer-focused resilience enhancement planning framework in power distribution systems considering a leader-follower approach under appropriate regulatory mechanisms. The regulator, distribution system operator (DSO), and customers are the key players in this framework, implemented through a three-step process. Firstly, the regulator establishes a penalty-reward model (PRM). Subsequently, the revenue-cap regulation is applied, and finally, customers' participation is incorporated through a leader-follower approach, modeled using a bi-level optimization problem. This approach considers the individual objectives of the DSO (as the leader) and interested customers to invest in self-generation (as followers), reflecting the accuracy, realism, and practicality of this framework since each entity looks for optimizing its own objective. Furthermore, the incentives provided by the DSO for customers' participation are directly modeled into the objectives of both the leader and followers. The proposed stochastic bi-level optimization problem, which takes the form of a mixed-integer linear programming (MILP) model, is solved using a reformulation and decomposition technique based on the column-and-constraint generation. Deploying the IEEE 33-bus test system exposed to a hurricane, the capability of the proposed framework is validated in enhancing the energy supply resilience under the regulatory objectives while achieving economic benefits for all involved entities.

Preparation and properties of short blade sodium ion batteries with Mg/Ti Co-Doped P2-type cathode materials

Accelerated study of CO2-ultrafine water mist to inhibit the compound flame at the early stage of gas/coal dust explosion

The RapidChek® Listeria monocytogenes NextDay™ Plus Test System was designed to detect Listeria monocytogenes on stainless steel and plastic environmental surfaces and in selected foods. It uses a proprietary enrichment followed by a lateral flow immunoassay to qualitatively detect L. monocytogenes. The aim of this study was to validate the Romer Labs RapidChek® Listeria monocytogenes NextDay™ Plus Test System against the USDA-FSIS-MLG and FDA-BAM cultural reference methods for the detection of L. monocytogenes in select foods including hot dogs, frozen breaded chicken, cured ham, ice cream and cooked shrimp, and on environmental surfaces including stainless steel and plastic (polyurethane, food grade) in an unpaired study design. The RapidChek® method uses a proprietary enrichment media system, a 44 to 48 h enrichment at 30 ± 1 °C and detects L. monocytogenes on an immunochromatographic lateral flow device within 10 minutes. Different L. monocytogenes strains were used to spike each of the matrices. Samples were confirmed based on the reference method confirmations and an alternate confirmation method. There were 82 RapidChek® presumptive positives matrices of which 81 were confirmed by the alternate confirmation method. The respective cultural reference methods produced 74 confirmed positives. All non-spiked samples were negative for Listeria monocytogenes by both methods. Probability of Detection (POD) analysis was performed and found no statistically significant differences between methods. The RapidChek® Listeria monocytogenes NextDay™ Plus Test System demonstrated performance comparable to the respective cultural reference methods while providing rapid results, supporting its use for monitoring L. monocytogenes in food and food processing environments. The method provides the end user with a rapid and reliable tool for monitoring and control of L. monocytogenes in RTE foods and environmental surfaces in accordance with their ongoing food safety needs.

To investigate the propagation and evolution characteristics of coal fractures, uniaxial compression tests were conducted on coal samples using a coal sample loading system and an acoustic emission (AE) testing system. AE parameters during loading were monitored to characterize coal damage and failure behaviors. PFC2D numerical software was employed to reconstruct fractured coal samples, enabling analysis of the micro-fracture propagation and evolution process under loading. The results indicate that coal samples undergo four sequential stages under uniaxial compression: initial stage, elastic stage, yield stage, and failure stage. Correspondingly, the internal fracture propagation and evolution of coal samples exhibits distinct stage-dependent features. In the initial stage, primary fractures within coal samples gradually tend to close under external loads. The elastic stage is characterized by minimal secondary fracture generation. When the external load reaches 80% of the coal sample's peak strength, the coal sample transitions from the elastic to the yield stage, accompanied by a sharp increase in AE ring counts and the initiation of internal fracture propagation and development. During the yield stage, internal fractures propagate and develop significantly, leading to a marked increase in coal volumetric strain. In the failure stage, fracture propagation and development culminate in the formation of a macroscopic fracture surface. Numerical simulation results demonstrate that secondary fractures inside coal samples experience a process from slow growth to rapid proliferation. Fractures initiate, propagate, and coalesce near or at the tips of primary fractures, ultimately resulting in coal failure.

Listeria monocytogenes presents a major challenge in the food industry. Routine monitoring is essential to ensure food safety in processing environments; therefore, rapid and reliable detection of Listeria is crucial for timely and effective intervention. To validate the RapidChek® Listeria NextDay™ Plus test system for the detection of Listeria monocytogenes, Listeria innocua, Listeria seeligeri, Listeria welshimeri, Listeria ivanovii, Listeria marthii and Listeria grayi in selected foods including hot dogs, frozen cooked breaded chicken and vanilla ice cream, and on environmental surfaces, including stainless steel, plastic, rubber, and painted concrete using an unpaired study design. The method uses a proprietary enrichment medium, a 24 to 48 h enrichment at 30 ± 1 °C and detects Listeria spp. on an immunochromatographic lateral flow device within 10 minutes. Listeria inoculated matrices were tested by the method, as well as the cultural reference method. The RapidChek method inclusivity was tested with 51 Listeria strains and its exclusivity using 30 non-target strains. Probability of detection (POD) analysis indicated no significant differences between the candidate method and the cultural reference method in the number of positive test portions detected for hot dogs, frozen cooked breaded chicken, stainless steel, plastic, and painted concrete. For vanilla ice cream and rubber, the candidate method yielded a greater number of positive test portions, with significantly higher POD values at the 95% confidence interval. Following enrichment, the RapidChek assay detected all 51 Listeria strains evaluated and produced no false positives among the 30 non-target organisms tested. The candidate method performed as well as the reference method in the detection of Listeria spp. on environmental surfaces after 24 h of enrichment and in selected food matrices after 27 h of enrichment. Enriching for 24-27 h yielded reliable presumptive results for Listeria spp.

A dynamic device to simulate intraarticular drug-release kinetics.

The integration of Distributed Generation (DG) in distribution networks introduces bidirectional power flows and fluctuating fault currents, severely compromising the selectivity of traditional overcurrent relays. To address this problem, an adaptive Multi-Agent System (MAS) integrated with Explainable Artificial Intelligence (XAI) using Shapley Additive Explanations (SHAP) is proposed. The proposed scheme dynamically recalculates Time Multiplier Settings (TMS) and Tap Settings (TS) using decentralized, local decision-making system. This eliminates the communication delay typical of centralized SCADA architectures while providing transparent, human-readable justifications for relay coordination. The proposed model was validated on the IEEE 69-bus test system using ETAP and MATLAB. Simulation results across 16 topological scenarios demonstrate that, whereas conventional fixed-setting approaches require a compromised TMS of 0.22 (delaying operation during low-fault events), the MAS autonomously adjusts the TMS

Long-distance pulling of submarine cables inside horizontal directional drilling (HDD) steel casings is often limited by high interfacial resistance, rapid pulling-force accumulation, and poor adaptability to muddy-sandy environments. In addition, conventional outward-extending roller devices are relatively bulky, which increases the required casing diameter and reaming size. To address these issues, this study proposes a compact ball-frame and tensioned steel cable series drag-reduction device. An 18 m local full-scale pulling test system was established using an actual engineering submarine cable, a practical-scale steel casing, and full-scale drag-reduction devices. The effects of pipe curvature, device spacing, terminal reaction force, and in-casing medium conditions on the equivalent friction coefficient were investigated. The results show that the equivalent friction coefficient of the submarine cable–steel casing system is maintained at 0.25–0.36 under most test conditions, which is significantly lower than the commonly adopted value of 0.55 for direct contact. Based on the experimentally identified parameters, a simplified assessment model for ultimate pulling length was established for construction scheme comparison and preliminary capacity estimation. The results indicate that, with the implementation of the tensioned steel cable series system, the ultimate pulling length increases from 431/696 m for direct pulling to 954/1424 m. These results provide valuable technical references for drag-reduction scheme selection and preliminary construction-capacity assessment in HDD landfall sections.

ABSTRACT The increasing integration of renewable energy sources into smart grids presents substantial challenges in solving the nonlinear and nonconvex optimal power flow (OPF) problem. This paper proposes a comprehensive OPF model that incorporates conventional thermal generators, solar photovoltaic generators, and hydroelectric power generators, while effectively addressing the uncertainties associated with renewable power generation. A lognormal probability distribution models solar irradiance variability in solar generators, while a Gumbel distribution captures water availability fluctuations in hydro generators. The paper proposes a novel hybrid optimization approach, hybrid osprey‐salp swarm optimization (HOSSO), to solve this complex OPF problem. The HOSSO leverages the exploration–exploitation balance of Osprey Optimization alongside the adaptive leadership and follower dynamics of Salp Swarm Optimization. The proposed methodology is validated on Institute of Electrical and Electronics Engineers 30‐, 57‐, and 118‐bus test systems across five distinct optimization scenarios: economic cost minimization, emission cost minimization, combined economic–environmental cost minimization, voltage deviation penalty cost minimization, and renewable generation uncertainty penalty cost minimization. The model incorporates reserve and penalty costs for renewable generation uncertainty and integrates carbon emission taxation to enhance grid reliability and sustainability. Comparative analysis against classical and hybrid optimization techniques demonstrates the superior performance of HOSSO across most test scenarios, consistently achieving competitive solutions while satisfying system constraints and stability requirements. The algorithm delivers improvements ranging from 0.4% to 17% in cost minimization, 3%–23% in voltage deviation minimization, and 2%–8% in uncertainty management over competing methods, with performance advantages becoming increasingly pronounced as system scale grows. The algorithm exhibits rapid convergence within 20–50 iterations, effectively avoids local optima, and proves well‐suited for both single‐ and multiobjective OPF problems in renewable energy‐integrated power systems. The results highlight HOSSO's potential for real‐time power system applications and its adaptability to smart grids with high renewable energy penetration.