Search Results (1,264)

During drilling circulation, the wellbore temperature field changes in response to drilling-fluid rheology, borehole geometry, drillstring eccentricity, and cuttings concentration. Conventional wellbore temperature models use fixed heat-transfer parameters and therefore cannot accurately represent real-time heat-transfer conditions. To address this limitation, a transient temperature model was developed. Bottomhole annular-fluid temperatures generated by OLGA were used as synthetic observations for MHE calibration. An MHE-based calibration method was developed to estimate the equivalent heat-transfer correction factor. The temperature model was first benchmarked against the Kabir analytical model and the commercial simulator OLGA. The estimated correction factor was then used by the mechanistic model to update the wellbore temperature field. The results showed that, under different initial values of the correction factor and assumed measurement-noise standard deviations, the equivalent heat-transfer correction factor converged to a steady-state value of approximately 0.941. Additional sensitivity tests showed generally stable calibration performance under moderate parameter settings, whereas stronger observation noise reduced calibration stability and accuracy. Under varying operating conditions, the calibrated bottomhole temperature yielded a mean absolute error of 0.033–0.332 °C, representing a reduction of 45.97–98.73% relative to the corresponding uncalibrated results. When the observation delay was extended to 2400 s (d = 8), the MAE was still reduced by 26.50–68.20% across different operating stages. These numerical results show that the proposed method can use bottomhole temperature observations to dynamically compensate for equivalent heat-transfer model mismatch under the investigated simulation conditions. The method reduces model-prediction errors and improves bottomhole temperature prediction under the tested varying operating conditions. The proposed method has potential applications in wellbore temperature prediction and high-temperature risk assessment for deep-well drilling. Full article

A unique V-grooved solar air collector was assessed experimentally and numerically to improve thermohydraulic performance. Experiments were conducted on the collector in Baghdad, Iraq, from 23 March to 3 April 2025, encompassing a mass airflow rate spanning 0.02 to 0.09 kg/s. The proposed design integrates wire mesh layers solely within the upper triangular channels, while the lower triangular channels remain unobstructed. A novel three-dimensional steady-state CFD model was originally developed for evaluating the thermohydraulic performance of a V-grooved solar air heater with and without wire mesh layers. The coupling between fluid flow and heat transfer models was implemented via the finite element method through the COMSOL Multiphysics program. The developed model for the collector incorporating wire mesh layers was validated experimentally, demonstrating strong agreement, with the greatest recorded root mean square error of 1.3597 °C for the outlet air temperature. The findings indicate that the enhanced collector attains a thermal efficiency enhancement of around 1.5 to 2.5 times relative to the baseline design, depending on operating conditions. The thermal efficiency attained levels up to 80%, whereas the thermohydraulic efficiency surpassed 70% at a moderate mass airflow rate. Despite the increase in pressure drops, the performance remained exceptional owing to the substantial enhancement in heat gain supported by the unique architecture. The results illustrate that the proposed design presents a viable solution for efficient solar air heating and can be adequately incorporated into near-zero-energy buildings. Full article

This study focuses on optimizing the quenching process for insoluble sulfur (IS) production, addressing the issues of high energy consumption and poor safety associated with the existing vaporization method. A process simulation model for a pilot-scale reactor was established using Aspen Plus V11. The research specifically investigated the influence patterns of three key parameters—the inlet temperature of the circulating liquid, the carbon-disulfide-to-sulfur (CS₂/S) mass ratio, and the mass ratio of circulating liquid to sulfur vapor—on the quenching effectiveness. Unlike previous Aspen Plus studies mainly directed toward overall IS production and recovery processes, the present work focuses specifically on the pilot-scale quenching stage and integrates single-factor thermodynamic analysis with a simulation-based orthogonal design to quantitatively rank the effects of the circulating liquid operating parameters. The orthogonal analysis showed that the mass feed ratio of circulating liquid to sulfur vapor was the dominant factor affecting the mixed temperature, followed by the circulating liquid inlet temperature, whereas the CS₂/S mass ratio had a comparatively smaller influence. Based on the simulated quenching behavior and thermodynamic constraints, the proposed process-level operating conditions were a CS₂:S mass ratio of 86:14–88:12, a circulating liquid inlet temperature of 50–56 °C, and a circulating liquid-to-sulfur vapor mass ratio of no less than 260:1. These results provide quantitative guidance for the steady-state optimization of the pilot-scale quenching process. Full article

Multiphase pumps are key equipment for the efficient transport of multiphase fluids in the petroleum industry, and their transient stability under variable-speed conditions directly affects system reliability. By combining numerical simulation with experimental validation, this study systematically investigates the evolution of external characteristics, energy conversion mechanisms, and the dynamic response of the internal flow field during a 0.4 s variable-frequency speed regulation cycle at inlet gas volume fractions (IGVFs) of 10% and 20%. The numerical model was validated against experimental measurements of a four-stage multiphase pump under pure-water steady-state conditions, with deviations in head, efficiency, and power all within 5%. The results show that during acceleration, the increase in hydraulic efficiency at the lower IGVF is greater than that at the higher IGVF; once deceleration begins, IGVF has no significant effect on hydraulic efficiency. At the investigated IGVFs of 10% and 20%, a higher IGVF increases the transient sensitivity of the internal flow field to speed variation, and increasing IGVF suppresses energy conversion in the impeller. The principal novelty of this work lies in the temporal decomposition of impeller work into dynamic and static pressure components during transient speed variation, revealing that static pressure power consistently accounts for more than 50% of the total power throughout the speed regulation cycle. As rotational speed increases, dynamic pressure power rises because the circumferential velocity of the fluid increases with impeller peripheral speed, while static pressure power also increases continuously owing to the enhanced static pressure work of the blades. During deceleration, the impeller’s energy transfer capability weakens with decreasing rotational speed, and both dynamic and static pressure power decline. These findings elucidate the coupled evolution of gas–liquid two-phase flow under variable-speed conditions and provide a theoretical basis for the operational optimization and speed control of multiphase pumps. Full article

Multi-product production systems require effective coordination among production, intermediate storage, downstream processing, and customer demand, particularly under stochastic operating conditions and finite capacity. Unlike existing analytical studies that mainly examine either single-product push–pull systems or multi-product manufacturing systems separately, this work develops an exact CTMC framework that jointly captures product variety, shared buffering, downstream parallelization, sequence-dependent setups, and machine unreliability. The system comprises an unreliable upstream machine with sequence-dependent setup changes, a finite intermediate buffer, a distribution center modeled as a pooled processing resource with (M) identical reliable channels, and dedicated finished-goods buffers serving product-specific demand. A high-dimensional continuous-time Markov chain is formulated, and a systematic algorithm is developed to construct the infinitesimal generator matrix and compute steady-state performance measures. Numerical experiments examine intermediate buffer capacity, downstream processing capacity, priority rules, and upstream machine reliability. Increasing buffer capacity from 0 to 20 increases total throughput from 0.5937 to 1.0988, whereas further expansion to 100 yields only 1.1606, while average work-in-process reaches 19.8524. Downstream capacity exhibits similar diminishing performance gains, while priority rules and machine reliability affect product-level and overall throughput. These findings highlight throughput–inventory trade-offs and demonstrate the framework’s applicability for evaluating alternative configurations. Full article

The transition toward sustainable energy systems requires reliable, efficient, and computationally practical control strategies for renewable energy-based microgrids. Grid-connected DC microgrids provide an effective platform for integrating distributed renewable energy resources, while their sustainable operation requires robust regulation under load variations, nonlinear loads, and input disturbances. This study proposes a lightweight Polynomial Regression Controller (PRC) for voltage regulation in grid-connected DC microgrids. The proposed data-driven controller uses a second-order polynomial model to estimate the converter duty cycle from input voltage, voltage error, and load current. The model is trained offline using independently generated operating trajectories and evaluated under previously unseen operating conditions. The results demonstrate accurate DC bus voltage regulation and robust operation under linear, constant power, motor load, and grid-connected conditions. The PRC maintains the DC bus voltage close to its 50 V reference, with steady-state errors of 0.002–0.008% and a settling time of 0.001 s under fast transient responses. The proposed approach combines nonlinear mapping capability with a compact computational structure, supporting practical implementation on resource-constrained platforms. Overall, the proposed PRC contributes to reliable renewable energy integration, resilient microgrid operation, and the development of sustainable, efficient, and scalable smart energy systems. Full article

In maritime navigation, precise and stable ship course control is critical for operational efficiency and maritime safety, yet it is severely challenged by unpredictable marine disturbances (e.g., waves, wind, and currents) that consist of slowly varying and stochastic components. Traditional control methods, though effective under specific operating conditions, exhibit limited adaptability to the nonlinear, time-varying characteristics of marine systems and inherent dependence on accurate ship mathematical models, which easily leads to suboptimal performance and elevated navigation risks, especially under sudden and intense disturbances. To address these limitations, this study proposes a novel control strategy, namely, model-free control integrated with super-twisting sliding mode control (MFSTSMC) with a linear extended state observer (LESO), for enhanced ship course control. Derived from the ultra-local model, the proposed method integrates the simplicity and practicality of model-free control, the real-time disturbance estimation and compensation capability of LESO, and the strong robustness of STSMC. The Lyapunov stability theory is rigorously employed to prove the stability of the entire control system, ensuring that the steady-state error converges to zero. Comparative analyses are conducted on an ocean ship verification platform, with strictly unified parameters for fairness. The comparative results evaluate the proposed method under three typical scenarios: course-keeping (small ±10° and large ±70° maneuvers), course tracking (low/high-frequency sinusoidal trajectories and high-frequency 20° abrupt change trajectory), and resistance to sudden escalating disturbances. The results demonstrate that the proposed MFSTSMC with LESO significantly outperforms existing controllers in terms of tracking accuracy, response speed, stability, and disturbance rejection capability. Its superior performance originates from the synergistic effect of real-time disturbance compensation and robust sliding mode compensation, which effectively mitigates the impact of model deviations and complex marine disturbances. This study provides valuable insights for the development of advanced marine navigation control strategies, and the proposed method exhibits promising engineering application prospects for ocean ship navigation in complex dynamic marine environments. Full article

Finite-buffer production systems are widely used in manufacturing, where performance depends on the interaction among machine reliability, buffer capacity, and maintenance policies. This study proposes a unified Continuous-Time Markov Chain (CTMC) framework for modeling and comparatively evaluating alternative finite-buffer production systems. Three configurations are considered: a serial production line with unreliable machines, a workstation-based system with parallel machines, and a condition-based maintenance system incorporating multi-state machine degradation and preventive maintenance. For each configuration, the state space, transition structure, infinitesimal generator matrix, and steady-state probability distribution are derived to estimate throughput, work-in-process inventory, cycle time, and total operating cost. Numerical experiments investigate the effects of buffer capacity, workstation parallelization, maintenance policies, degradation severity, reliability parameters, and financial factors. Under the baseline setting, the conventional serial configuration achieves a throughput of 0.8300 products/min, while workstation parallelization increases throughput to 1.6840 products/min, corresponding to a 102.9% improvement. The condition-based maintenance configuration achieves 0.8173 products/min while accounting for equipment deterioration and preventive-maintenance interventions. Overall, the framework enables the consistent evaluation of operational and economic trade-offs and supports production planning, maintenance optimization, and manufacturing system design. Full article

The increasing popularity of electric vehicles is inevitable due to their lower dependence on conventional fuel and reduced air pollution. Among various drivetrain architectures, four-wheel independently driven electric vehicles (4WID-EVs) have gained significant attention owing to their superior load-carrying and dynamic performance. However, the distributed four-motor architecture makes them vulnerable to unpredictable motor failures, necessitating an effective fault-tolerant control strategy. This work proposes a common sliding mode controller (CSMC)-integrated quantum complete graph neural network (QCGNN) for adaptive tuning under one-, two-, and three-motor failure conditions at reference speeds of 20 and 40 m/s, ensuring stable operation through continuous state feedback. Simulation results demonstrate fault recovery within 3 s, a rise time of 1.2–1.3 s, a settling time below 5.5 s, a peak overshoot below 8%, and a steady-state error below 0.2%. Compared with the QCGNN-Optimal LQR, the proposed QCGNN-CSMC reduces the Mean Absolute Error (MAE) from 34 to 18, Root Mean Square Error (RMSE) from 41 to 23, and the steady-state error from 1.07 to 0.56, while maintaining R² values above 0.90. Rapid controller prototyping further validates the robustness, reliability, and real-time applicability of the proposed fault-tolerant control framework for 4WID-EVs. Full article

This research presents a comparative performance evaluation of two advanced maximum power point tracking (MPPT) methodologies, namely sliding mode control (SMC) and the Kalman filter (KF), specifically applied to a standalone photovoltaic water pumping system (PVWPS). To achieve economic viability, the system is designed for storage-less operation, driving a three-phase induction motor (IM) via a high-dynamic direct torque control (DTC) scheme and a three-level inverter. The core technical contribution addresses the critical challenge of maximizing energy yield under partial shading conditions (PSCs). PSCs result in a complex, non-convex power–voltage (P−V) characteristic, containing multiple peaks, where conventional MPPT algorithms fail to consistently locate the global maximum power point (GMPP). To overcome this deficiency, we implemented the SMC-based MPPT algorithm to exploit its inherent robustness and rapid dynamic response, and compared it with the Kalman filter MPPT, which relies on stochastic state estimation to achieve accurate tracking and effective disturbance rejection. MATLAB/Simulink analysis compares the proposed techniques with the perturb and observe (P&O) MPPT method. The comparison considers tracking efficiency, convergence speed, and steady-state ripple under various shading conditions to identify the most effective control strategy for improving PVWPS performances. The reported performance evaluations are based on numerical simulations conducted within the MATLAB/Simulink environment, using a validated system model. Full article

To address rapid frequency decline, transient voltage violations, and excessive configuration costs caused by competition between active and reactive power support in weak grids, this paper proposes an optimal configuration method that incorporates the fault-period voltage-support capability of photovoltaic (PV) inverters into the planning of a grid-forming energy storage system (ESS). A coordinated response model for the ESS and PV inverter is developed, in which the PV inverter provides reactive power through Q-V droop control while smoothing its active power output. An optimization model is then formulated to minimize the annualized ESS cost while satisfying constraints on transient frequency security, voltage recovery, islanded operation, and state of charge (SOC). Frequency security indices, including the rate of change in frequency, frequency nadir, and quasi-steady-state frequency deviation, are explicitly linked to the rated power and energy capacity of the ESS. A hierarchical solution framework integrating capacity search, scheduling while connected to the grid, stepwise transient verification, and steady-state assessment under islanded operation is adopted to improve computational efficiency. Case studies on a weak distribution network show that PV transient voltage support reduces the reactive power requirement of the grid-forming ESS and lowers its configuration cost by approximately 5.2%. Meanwhile, all frequency and voltage indices remain within the prescribed security limits. Further multi-scenario evaluations and sensitivity analyses confirm the broader applicability of the proposed method across different operating conditions. Full article

The dual active bridge (DAB) converter is one of the most common types of isolated bidirectional power converters in modern spacecraft EPS owing to its galvanic isolation, bidirectionality, soft switching, and good controllability. However, the goal of power transfer maximization often clashes with real-world spacecraft EPS constraints, namely thermal compliance, reliability, and the accuracy of simplified models used for analysis. This paper proposes a physics-informed methodology to derive the practical operating range under single phase shift (SPS) control based on a rigorous piecewise time-domain representation. From this model, the steady-state initial condition, general closed-form RMS current expression, ZVS boundary condition, and ZVS-aware loss model linked to the junction-temperature estimate are derived. The validity domain of the fundamental harmonic approximation (FHA) is evaluated against the exact model across the full (φ, k) space, and a two-dimensional operating map superposing power contours, the ZVS limit, and the thermal limit is presented. For the baseline case study at k = 1.0, the thermal constraint limits the nominal feasible upper phase shift to approximately 35°, while the broader 15–45° range remains useful for design assessment and operation toward 45° requires lower effective resistance and/or improved thermal management. The normalized SPS power-transfer curve retains the same shape under variations in L and f_s, but RMS current, losses, and thermal feasibility must be reassessed for each converter design. The resulting closed-form framework provides a steady-state feasibility-evaluation tool for spacecraft EPS design and offers a computational basis for future supervisory constraint evaluation under varying voltage, load, and thermal conditions. Full article

This study investigates how the insertion point and parameterization of reinforcement-learning (RL) compensation affect a low-voltage dual-active-bridge (DAB) converter operated with triple-phase-shift (TPS) modulation. A proportional–integral (PI)-TPS controller is used as the common baseline. Two deep deterministic policy gradient (DDPG) compensation structures are compared: one directly corrects the three TPS variables, whereas the other corrects the high-level phase-shift command before the deterministic TPS mapping. The controllers are evaluated at the rated point and under fixed and stepwise input-voltage and load variations. Direct three-variable correction provides no consistent improvement in the investigated simulations, while phase-shift-level compensation provides a more favorable voltage-current tradeoff and preserves TPS coordination. At the rated point, the phase-shift-level scheme reduces the steady-state voltage error by 29.34%, and the full-transient peak inductor current from 69.82 to 36.84 A. Variable-condition results represent robustness after retraining rather than zero-shot generalization. Because the two RL formulations also differ in observations and rewards, the comparison concerns the complete compensation structures rather than action-space dimension alone. Full article

Aiming at the problems of large speed synchronization error and prominent speed overshoot existing in conventional PID control algorithms widely adopted for diesel-engine parallel-unit speed-governing systems, this paper proposes a speed control algorithm based on Model Predictive Control (MPC) for dual-diesel-engine parallel operation. A quasi-steady-state method is employed to establish the coupled state-space model for dual-engine parallel operation. Leveraging the prediction-optimization and multi-constraint regulation characteristics of MPC, the fuel-injection outputs of the two diesel engines are regulated respectively by two independent SISO MPC controllers, which share the identical speed reference and are coordinated at the logic level through the Stateflow engagement/disengagement state machine to achieve speed synchronization. Comparative simulations under different operating conditions are carried out on the Matlab/Simulink platform. The simulation results show that the proposed MPC algorithm can effectively suppress speed fluctuations between the two diesel engines under the tested operating conditions compared with the traditional PID control. Furthermore, a hardware-in-the-loop test platform is constructed for validation in the embedded environment. The test results reproduce all operating conditions of offline simulation, achieving zero speed overshoot and restricting the dual-engine synchronization deviation within ±3 rpm, which are consistent with the offline simulation results. The real-time computational capability and engineering feasibility of the proposed algorithm are therefore verified. The proposed method is applicable to stable speed-governing scenarios of marine dual-diesel-engine parallel-unit sets. Full article

To proactively identify performance anomaly evolution and potential operational risks of marine main engines and reserve a sufficient time window for maintenance intervention, this paper proposes a data-driven multi-algorithm fusion framework for performance evaluation and anomaly early warning of marine main engines. The framework first adopts a steady-state detection strategy to filter valid operating conditions and introduces the CLIQUE clustering algorithm to realize adaptive partitioning of high-dimensional operating parameters; comparative experiments with the classical K-means++ clustering algorithm demonstrate that CLIQUE achieves finer-grained operating condition classification without pre-defining the number of clusters and better adapts to the uneven distribution of actual marine engine operating conditions, which addresses the limitations of traditional single-parameter analysis and conventional dimensionality reduction methods in practical shipboard scenarios. On this basis, the Mahalanobis distance evaluation model is constructed under each partitioned operating condition, which further improves the stability and anti-interference performance of quantitative performance assessment for the main engine. Meanwhile, by integrating cumulative anomaly trend analysis and the Yamamoto mutation test, the framework accurately captures statistical mutation characteristics of the performance deviation trajectory and identifies the first mutation point as the retrospective candidate change point, forming a systematic anomaly detection mechanism. Validation using field measurement data from a 6RT-flex82T marine main engine shows that the proposed framework can comprehensively characterize the overall operating state of the main engine and capture long-term performance deviation evolution patterns. Retrospective analysis indicates that the first statistical mutation of the multivariate performance deviation precedes the significant abnormal fluctuation of a single parameter by approximately 20 days, showing the potential of providing a maintenance buffer period. The proposed method can provide technical reference and support for condition-based maintenance of marine main engines and intelligent operation and maintenance of shipboard power equipment. Full article