We address the problem of geolocating a static ground target from multiple low-cost Unmanned Aerial Vehicles (UAVs) equipped with monocular cameras and object detectors. Each drone generates large sequences of bearing-only measurements per flyover, but these are affected by per-drone GPS biases (systematic position errors specific to each UAV) that remain effectively constant over short trajectories. We propose a greedy selector that combines angular diversity and detection confidence to pre-filter measurements before Random Sample Consensus (RANSAC)-based robust fusion. Across 30 randomized simulation runs, the selector achieves mean accuracy comparable to full-pool RANSAC (2.34 m vs. 2.44 m) while reducing median processing time by 4.1× (393 ms vs. 1602 ms). Similar accuracy is observed against LO-RANSAC and PROSAC, with the selector remaining 4× to 35× faster. The selector also outperforms confidence-only and standard Fisher Information Matrix (FIM)-based subset baselines. A bias-aware FIM analysis via Schur-complement marginalization shows that the information contributed by repeated measurements from a single drone saturates under a shared position bias, explaining the single-drone concentration observed for these baselines. In the nominal setting, the angular-diversity proxy retains 99.7% of the bias-aware FIM objective and achieves localization error similar to direct FIM-based selection, while being 3.3× faster at the selection stage. Real flights with a low-cost quadrotor measure short-term GPS drift of 1.9–3.5 m over 10–63 min, supporting the assumed bias dynamics, and expose a failure mode in which persistent false positives capture the RANSAC consensus. Full-pool RANSAC shows slightly lower mean error at larger GPS-bias levels (σGPS ≥ 5 m), indicating that pre-selection is not preferable in every operating regime.
Green chemistry has evolved from a pollution-prevention concept into a practical framework for sustainable chemical manufacturing. To address climate change, resource depletion, and environmental pollution, chemical processes must be redesigned beyond end-of-pipe treatment toward low-carbon, safer, and circular manufacturing systems. This mini-review develops a systems framework for low-carbon and circular technologies in chemical manufacturing by organizing green chemical technologies into four interrelated pathways: feedstock transition, catalysis and reaction engineering, process intensification and electrification, and circular product design. Quantitative metrics such as atom economy, E-factor, process mass intensity, carbon footprint, and life-cycle assessment are emphasized as essential tools for evaluating real sustainability benefits and avoiding burden shifting. The review further highlights the enabling roles of biocatalysis, artificial intelligence, predictive modeling, digital twins, automation, and systems engineering as cross-cutting tools for translating technological advances into industrial-scale sustainable manufacturing. Future green chemical technology should move from isolated greener reactions toward integrated molecular, process, and system design for low-carbon and circular chemical manufacturing.
The rising need for economical and ecologically friendly bridges calls for practical solutions that do not compromise the strength, utility, and safety of the structures. The steel-concrete bridge system uses steel girders that carry most of the weight. Thus, an optimal arrangement of girders is necessary for structural efficiency and economic advantage. This study investigates the structural optimization of steel main girders for composite bridges to obtain optimum structural weight and economy. To investigate the coupled behavior of steel girders and concrete decks under realistic conditions, Finite Element Modeling (FEM) is used. In this approach, alternative sizes or configurations for the steel girder are evaluated to predict tensile and compressive stresses as well as deflections. This involves a comparison between the material savings and cost benefits of optimized or conventional designs/configurations. The optimization approaches used in designing composite bridges seem effective at reducing steel mass without affecting bridge performance in terms of stresses and deflections. This study shows that cross-sectional and topology optimization result in a bridge that is more economical, using less steel than previous bridges. Optimization techniques are suggested for designing and building bridges, especially large-scale projects, because of their importance in providing cost-effective and energy-efficient solutions.
This paper suggests an analytical framework to design the output impedance of a microsource inverter to meet the requirements of proportional load sharing with the permissible range of THD (total harmonic distortion) of the output voltage as per the IEEE 519 standard. In order to achieve the aforementioned objectives, the integral controller is designed in such a way as to make the output impedance of an inverter capacitive in nature. The optimum design of capacitive output impedance at the harmonic frequencies ensures reduced THD levels in the output voltage without affecting proportional load sharing, which is determined by fundamental frequency impedance, ensuring the decoupled design to meet different requirements at the same time. The focus of the work is also laid on the inherent limitations of conventional droop control of inverters and its remedial measures through bolting a regulator on its control loop. The modification of the robust droop control structure for a capacitive inverter is discussed, and small signal stability/PF (participation factor) based analysis is done to ensure the steady state stable operation. In order to enhance the load voltage quality further, a bypassing the harmonic current components strategy is discussed and developed further, which led to THDv < 5%. Subsequently, the basic stability analysis is conducted to determine the finite parameters of BHC by control system principles. The discussed models and schemes are simulated under both linear and nonlinear load conditions to validate the proposed strategies, and their effectiveness is assessed through a comparative analysis.
This paper presents an optimal switching strategy and a cost-effective hybrid configuration employing silicon (Si) IGBTs and silicon carbide (SiC) MOSFETs in a three-level active-neutral-point-clamped (ANPC) converter for high-power off-board electric vehicle (EV) chargers. A three-stage switching scheme is proposed to achieve balanced current sharing and minimize switching losses over a wide load range. In addition, a cost-saving function (CSF) is introduced to quantify the total lifecycle cost of the converter utilizing hybrid parallel switch sets, encompassing both the initial device procurement cost and the operating cost arising from power losses over the system lifetime. The proposed CSF effectively identifies the optimal hybrid switch configuration for the ANPC converter. PLECS simulations using actual device data and characteristics from multiple suppliers demonstrate that the proposed design achieves up to a 12.02% reduction in power losses compared with single-Si-switch designs and a 66.42% cost saving relative to all-wide-bandgap solutions, thereby providing an effective efficiency–cost trade-off for next-generation EV charging systems.
