Fast investigation of control interaction risks in PV parks using eigenvalue analysis in Modelica

This paper contributes to the fast detection of control interaction risk in a PV park using the eigenvalue analysis in Modelica. The entire PV park and its interconnected network are represented by time-domain equations in Modelica, then linearized state space equations are extracted directly by leveraging the Modelica features. This constitutes an advantageous approach for fast finding eigenvalues and extracting potential instability conditions. The presented approach is verified with electromagnetic transient (EMT) simulation and impedance-based stability analysis (IBSA) that uses EMT-type impedance scanning methods. The results show an outstanding improvement in the simulation time and accuracy

ROBOtic Replicants for Optimizing the Yield by Augmenting Living Ecosystems

As the world’s most successful pollinators, bees play a huge part in every aspect of the ecosystem. So, any decline in bee populations could pose a threat to global agriculture. In this context, the EU-funded RoboRoyale project is developing and combining micro-robotic, biological and machine learning technologies into a system that can support the well-being of the honeybee queen, which is responsible for the reproductive success and efficiency of a colony. Specifically, the micro-robotic system will operate around the queen. For instance, this multi-robot system will replace the court bees that are in charge of feeding, grooming and cleaning of the queen as well as the facilitation of pheromone transfer from the queen to the workers.Funded under Horizon 2020 Framework Programme, H2020-FETOPEN-2020-0

Terahertz frequency-domain characterization of UHMW-PE ballistic armor plates

Ultra-high molecular weight polyethylene (UHMW-PE) fiber-based ballistic armor plates are analyzed in the terahertz (THz) frequency region to better understand their structural properties. Various thickness plates are produced by hot pressing 5, 10 and 15 layer four-ply cross-weaved UHMW-PE fiber sheets whose refractive index and absorption characteristics are then examined for three different frequencies using time-domain imaging techniques. The obtained transmission images reveal significant structural information, including surface texture and potential defects, such as air bubbles or voids. It is found that with an increasing number of layers in each plate there is an increase in the refractive index approaching the value of the UHMW-PE fiber sheet. The change in the effective refractive index is attributed to inhomogeneities such as bunching up of the fibers as well as voids because of the manufacturing processes with a larger inhomogeneity in the 5-layer plates as compared to the 10-and 15-layer plates. Furthermore, a significant change in refractive index is observed for different orientations of the armor plate with respect to the input beam polarization due to the presence of periodic surface ridge formations. A detailed analysis of the extinction coefficient with respect to the refractive index shows groupings in the range of values for different thickness plates which can serve as an indicator of the inhomogeneities inside the structures. The purely frequency domain analysis performed here suggests that such methods in the THz region can offer a new, rapid way for non-destructive analysis of ballistic armor plates

Insight into greenhouse gas emission in freshwater aquaculture ponds in Jiangsu Province: Variation due to species used and ponds management practice

Aquaculture ponds have emerged as a significant contributor to greenhouse gas (GHG) emissions. We measured methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) emissions in ponds, all located in Jiangsu Province, with different fish and management practices over an entire cycle. All ponds emitted these gases, with higher CH4 and N2O levels during fish growth than stocking period. The highest CH4 and N2O fluxes were found in the Crucian carp (Carassius auratus) pond with up to 16,512 +/- 3015 mu mol/(m(2)h) and 5.54 +/- 0.31 mu mol/(m(2)h), respectively. CH4 was the primary contributor to the global warming potential in traditional earthen ponds, accounting for an average contribution rate of 87.7 %. The dissolved oxygen (DO) concentration was the water quality parameter that most significantly influenced the CO2 flux, while pH acted as its primary regulator. The GHG emission intensity per unit of fish production in traditional earthen ponds was 197 times higher than that in-pond raceway systems. Largemouth bass (Micropterus salmoides) and Crucian carp ponds exhibited CH4 diffusion fluxes at the sediment-water interface, which were > 20 times higher than those at the water-air interface. Our results further suggest that stocking density and feed amount significantly influence the variations in GHG emissions among the ponds with the in-pond raceway system having low carbon emissions and being high yield aquaculture system compared to traditional earthen ponds. The water depth and DO concentration can be manipulated to reduce GHG emissions across the various interfaces

Integrating solutions for enabling the sustainable development of energy, water and environment systems

The world has reached 1.24 degrees C of global warming above pre-industrial levels when averaged over the last decade, necessitating time-saving options for the mitigation of climate change. Within a long-term scientific pursuit for integrating solutions, the 19th Conference on Sustainable Development of Energy, Water and Environment Systems was organised in Rome, Italy, in 2024 alongside the regional 4th Latin American and 2nd Asia Pacific Conferences in Chile and Australia, respectively. The thematic coverage of this review-style editorial represents the key findings of the 22 original articles in this special issue, synthesized into six themes. Demand flexibility within decarbonisation processes includes end-use electrification scenarios in renewable energy communities, probabilistic load coordination, and optimising district heating and/or cooling systems. Securing cross-sectoral benefits with renewable energy extends to locating data centres based on community infrastructure needs for clean energy access and clean drinking water, better interconnector capacity, solutions for maritime transport, and tackling environmental pollution and electronic waste. Advances in green hydrogen supply and value chains span a co-simulation framework with solar energy and repurposing for green hydrogen stations, among others. For improving energy storage and waste heat utilisation, new battery energy storage systems, an energy targeting approach linking industry and buildings, and the utilisation of waste heat from water electrolysis are explored. Technological advances and enhanced heat transfer are then supported by findings for parabolic trough solar collectors with nanofluids, building thermal energy load prediction, and optimising heat exchanger design. These advances take place alongside those for marine energy by optimising large-scale, multi-gigawatt offshore wind farms, also considering aspects of public acceptance and options for energy system restructuring. The integrated solutions that are represented within these advances and their broader synthesis provide ample opportunities for mitigating climate change, providing benefits for improving livelihoods, and securing a safer climate future on this shared planet

A local correlation-based algebraic transition model in k-ω SST formulation

A new correlation-based algebraic transition model using local variables is proposed. Instead of solving an additional transport equation for intermittency, the model employs an intermittency function that controls the source terms of the turbulence model used. Thus, the model reduces the number of constants and functions needed, and achieves to solve problems by using less computational power compared to one-or two-equation transition models. The intermittency function of the present model is a more sophisticated modified version of that in the SA-BCM transition model, and it is coupled with the k-w SST turbulence model to eliminate the shortcomings in the SA-BCM model. The present model involves only four calibration constant, which are calibrated against the cases other than validation cases. The model is validated against a series of common flat plate experiments and four airfoil test cases. The results show a good agreement with the experiments and that the new model provides comparable success with more complicated transition models. Therefore, the present model provides an alternative means to include boundary layer transition effects in CFD simulations by reducing the number of constants and functions needed compared to that in other transition models

Strut and tie models with the dual use of the finite element method and the lattice networks

Strut and tie modelling (STM) is widely recognized as a prominent design method for the design of disturbed (D) region reinforced concrete structural elements. The paramount initial step in conducting optimized reinforcement designs lies in the establishment of strut and tie geometry. In this study, a novel dual modelling approach is proposed, combining two distinct models, namely the continuum model (specifically, a finite element model) and the lattice network (comprising overlapping truss elements interconnected at every two nodes). The approach involves the application of a novel element removal algorithm based on the computed internal forces and stresses for the two lattice and finite element models working in tandem while sharing information. The iterative process continues until the convergence of the internal energy of the reduced lattice network. To evaluate the accuracy and efficacy of the proposed approach, a comprehensive demonstration is conducted employing the 20 most extensively studied design examples documented in the literature. The findings indicate that the dual system is a viable alternative method for STM design by satisfying the minimum energy requirements and without conducting laborious nonlinear finite element analysis. Furthermore, objective designs are possible from the derived STM models which can used in automated design flows

The social reactive and/or reasoned acceptance of the intelligent speed adaptation system in Türkiye and Israel

Technology has become important in solving the problem of speeding. One technological advancement aimed at overcoming the speeding problem is the Intelligent Speed Adaptation (ISA) system. Although the ISA systems enhance traffic safety, the standard role of drivers in driving is challenged by these systems. Therefore, driver acceptance of such systems is essential for their implementation, which may be dependent on the country's driving climate and other characteristics, such as road fatality rates and gross national income. The current study therefore examines the utility of an integrative model of the Theory of Planned Behavior (TPB) and the Prototype Willingness Model (PWM), which are two popular decision-making frameworks, comparing participants from two different countries which may differ in their driving climate and which is important to the external validity of the results. This study is the first to test this model in two countries. A total of 334 drivers from T & uuml;rkiye and 359 drivers from Israel completed a questionnaire by way of an online link. The results show that the integrative model explains the highest variance in preference for using the informative type of the ISA in both countries. In addition, the model explains a higher variance in preference for using the informative and intervening types of the ISA in Israel and the supportive type of the ISA in T & uuml;rkiye. Although the integrative model differed between the two countries, intention was the strongest predictor of preference in using all types of the ISA. However, as control of the system increases, the socialreactive path becomes more prominent in T & uuml;rkiye, whereas the reasoned path becomes significant in Israel. Finally, attitude is an additional important predictor of preference in Israel, whereas prototype perceptions are more prominent in T & uuml;rkiye. The results and the implications are discussed in light of the literature

Nonlinear vibrations and modal interactions in rotating pre-twisted blades with thickness and chord variations using high-fidelity models with DICFs and PA

This study presents a high-fidelity investigation into the coupled in-plane and out-of-plane nonlinear vibration characteristics and modal interactions of rotating pre-twisted blades with variable thickness and chord length. A geometrically nonlinear structural model is developed based on first-order shear deformation theory, with all nonlinear terms of the Green's strain tensor retained to accurately capture large deformation effects. The formulation is constructed within a surface-based framework that incorporates pre-set, pre-twist, spanwise and chordwise cross-sectional variation, and chord tapering. Two centrifugal stiffening strategies, i.e., Direct Integration of Centrifugal Forces (DICFs) and Pre-Stressed Analysis (PA), are systematically compared to evaluate their influence on both free and forced vibration responses. The spatial domain is discretized using the Spectral Chebyshev Technique (SCT), allowing a high number of modes to be retained across complex geometries. An enhanced reduced-order modeling framework is employed to preserve key nonlinear restoring forces and multi-mode interactions. The resulting equations are solved using the harmonic balance method with arc-length continuation to compute steady-state solutions and nonlinear frequency response curves. Numerical results reveal significant differences in resonance behavior and internal modal couplings under different centrifugal stiffening assumptions. This comprehensive approach offers new insights into the nonlinear dynamics of rotating blades, highlighting the critical influence of modeling strategy and model order on accurately capturing the full spectrum of nonlinear dynamics

Evaluating confidence in geometric matching between 3D point clouds and BIM models by integrating coverage, distance, and distribution metrics

Accurate and objective assessment of the matching of a Building Information Model (BIM) with 3D point cloud data (PCD) is critical to Scan-to-BIM and Scan-vs-BIM workflows. However, existing methods for PCD-BIM matching evaluation do not fully and robustly account for geometric accuracy and spatial completeness. This paper introduces a statistically-grounded method that combines three indices that complementarily assess matching Coverage, Distribution, and Distance. The proposed method also accounts for inter-element occlusions when calculating each element's theoretically visible surface, which increases the metrics' reliability. Validation is conducted across 46 PCD-BIM pairs, encompassing 4000+ elements from ISPRS, CV4AEC, BIMNET and custom datasets, as well as a residential building case study comparing manual and automated BIM model reconstructions, and demonstrating the applicability of the method to any type of element. Results show practical value for both Scan-to-BIM and Scan-vs-BIM practice and enable quantitative assessment of benchmark dataset quality via the proposed indices