Search Results (381)

Permafrost degradation, driven by the thawing of ground ice, results in the progressive thinning and eventual loss of the permafrost layer. This process alters hydrological and ecological systems by increasing surface and subsurface water flow, changing vegetation density, and destabilising the ground. The thermal and hydraulic conductivity of permafrost are strongly temperature-dependent, both increasing as the soil warms, thereby accelerating thaw. In addition, thawing permafrost releases large quantities of greenhouse gases, establishing a feedback loop in which global warming both drives and is intensified by permafrost loss. This paper reviews the mechanisms and consequences of permafrost degradation, including reductions in strength and enhanced deformability, which induce landslides and threaten the structural integrity of foundations and critical infrastructure. Permafrost has been investigated and modelled extensively, and various approaches have been devised to address the consequences of thawing permafrost on communities and the built environment. Some techniques focus on keeping the ground frozen via insulation, while others propose local replacement of permafrost with more stable materials. However, given the scale and pace of current changes, systematic remediation appears unfeasible. This calls for increased efforts towards adaptation, informed by interdisciplinary research. Full article

Community Earth System Model-Large Ensemble (CESM-LE) simulations are used to partition the Surface Air Temperature (SAT) trends over East Asia into the contribution of external forcing factors and internal variability. In the historical period (1966–2005), the summer SAT trends display a considerable diversity (≤−2 °C to ≥2 °C) across the 35 member ensembles, while under the RCP8.5 scenario, the region is mostly dominated by a strong warming trend (~1.5–2.5 °C/51 years) and touches the ~4 °C mark by the end of the 21st century. In the historical period, the warming is prominent over the Yangtze River basin of China, while under the RCP8.5 scenario, the warming pattern shifts northward towards Mongolia. In the historical period, the Signal-to-Noise Ratio (SNR) is less than 1, while it is higher than 4 under the RCP8.5 scenario, which indicates that, in the early period, internal variability overrides the forced response and vice versa under the RCP8.5 scenario. In addition, over much of the East Asian region, the chances of cooling are relatively high in the historical period, which partially counteracted the warming trend due to external forcing factors. In contrast, under the RCP8.5 scenario, the chances of warming reach ~100% over East Asia due to contributions from the external forcing factors. The novel aspect of the current study is that, in the negative phase (from the mid-1960s to ~2000), the Atlantic Multidecadal Oscillation (AMO) accounts for ~70–80% of the cooling trend or the SAT variability over East Asia, and thereafter, natural variability exhibits a slow increasing trend in the future. However, the contribution of external forcing factors increases from ~55% in 2000 to 95% in 2075 at a rate much faster than natural variability, which is primarily due to increasing downward solar radiation fluxes and albedo feedback on SAT over East Asia. Full article

Gallium-based room-temperature liquid metal is a promising multifunctional material for microfluidics and precision machining due to its high mobility and deformability. However, precise motion control of gallium-based liquid metal droplets, especially in abrasive particle-laden fluids, remains challenging. This study presents a hybrid control framework for regulating droplet motion in a one-dimensional PMMA channel filled with NaOH-based SiC abrasive suspensions. A dynamic model incorporating particle size and concentration effects on the damping coefficient was established. The system combines a setpoint controller, high-resolution voltage source, and vision feedback to guide droplets to target positions with high accuracy. Experimental validation and MATLAB simulations confirm that the proposed dynamic damping control strategy ensures stable, rapid, and precise positioning of droplets, minimizing motion fluctuations. This approach offers new insights into the manipulation of gallium-based liquid metal droplets for targeted material removal in micro-manufacturing, with potential applications in microelectronics and high-precision surface finishing. Full article

Sludge dewatering remains a resource-intensive process, often constrained by high residual moisture content and inefficient chemical conditioning. Conventional systems typically rely on fixed polymer dosages and predetermined filtration pressures, which are unable to respond to variations in sludge characteristics, resulting in inconsistent and suboptimal performance. In this study, a real-time control system for municipal wastewater sludge dewatering was developed to dynamically regulate coagulant dosing and filtration pressure based on continuous monitoring of critical sludge parameters, including total solids (TS), viscosity, sludge temperature, and pH change following coagulant addition. The control logic, derived from empirical correlations between sludge dewaterability metrics such as time-to-filter (TTF) and capillary suction time (CST) and operational variables, enables adaptive adjustment of polyoxyethylene alkyl ether (POAE) injection and pressing conditions. Implementation of this system achieved a final cake moisture content of approximately 63% after 60 min of filtration, substantially lower than the ~84% moisture observed under static conditions. Real-time flux feedback facilitated timely pressure escalation (from 15 to 20 bar to 25–30 bar), improving water removal efficiency while avoiding premature cake blinding. The pH drop (~0.7 units) post-polymer addition served as a practical indicator of adequate flocculation, supporting dose optimization and minimizing chemical waste. The proposed system demonstrated enhanced dewatering performance, reduced polymer consumption, and greater operational robustness compared to conventional approaches. These findings highlight the potential of integrated sensor-based control to advance sludge treatment technologies by promoting smarter, adaptive, and resource-efficient dewatering operations. Full article

This research presents the design and implementation of a cascade Proportional–Integral (PI) controller tailored for a Variable Air Volume (VAV) system that was specially created and executed particularly for hospital operating rooms. The main goal of this work is to make sure that the temperature and positive pressure stay within the limits set by ASHRAE Standard 170-2017. This is necessary for patient safety, surgical accuracy, and system reliability. The proposed cascade design uses dual-loop PI controllers: one loop controls the temperature based on user-defined setpoints by local control touch screen, and the other loop accurately modulates the differential pressure to keep the pressure of the environment sterile (positive pressure). The system works perfectly with Building Automation System (BAS) parts from Automated Logic Corporation (ALC) brand, like Direct Digital Controllers (DDC) and Web-CTRL software with Variable Frequency Drives (VFDs), advanced sensors, and actuators that give real-time feedback, precise control, and energy efficiency. The system’s exceptional responsiveness, extraordinary stability, and resilient flexibility were proven through empirical validation at the Korean Iraqi Critical Care Hospital in Baghdad under a variety of operating circumstances. Even during rapid load changes and door openings, the control system successfully maintained the temperature between 18 and 22 °C and the differential pressure between 3 and 15 Pascals. Four performance scenarios, such as normal (pressure and temperature), high-temperature, high-pressure, and low-pressure cases, were tested. The results showed that the cascade PI control strategy is a reliable solution for critical care settings because it achieves precise environmental control, improves energy efficiency, and ensures compliance with strict healthcare facility standards. Full article

As robotic systems advance in autonomy and sophistication while being used in uncertain environments, the challenge of building reliable and robust electric motors that are embedded into robotic systems has never been a more important engineering problem. Thermal distress caused by extended operation or excessive loading can negatively affect a motor’s performance and efficiency and lead to catastrophic hardware failure. This paper proposes a novel intelligent control framework that includes real-time thermal feedback for hybrid electric motors that are embedded into robotic systems. The framework relies on adaptive control techniques and lightweight machine learning techniques to estimate internal motor temperatures and dynamically change operational parameters. Unlike traditional reactive methods, this framework provides a spacious active/predictive method of heat management, while preserving efficiency and allowing for responsive control. Simulations, experimental validations, and preliminary trials that deployed real robotic systems demonstrated that our framework allows for reductions in peak temperatures by up to 18% and extends motor lifetime by 22%, while retaining control stability and a range of variations in PWM adjustments of ±12% across disparate workloads. These results demonstrate the efficacy of intelligent and thermally aware motor control architectures and processes to improve the reliability of autonomous robotic systems and open the door for next-generation embedded controllers that will allow robotic platforms to self-manage thermal effects in resilient, adaptable robots. Full article

Accurate temperature regulation is essential in microfluidic apparatus, particularly for procedures such as polymerase chain reaction (PCR), cellular analysis, and chemical reactions that rely on stable thermal conditions. However, achieving temperature uniformity at the microscale remains challenging due to rapid heat dissipation, small thermal mass, and intricate flow–heat interactions. This work reviews contemporary methodologies to enhance thermal control in microfluidic systems, including proportional–integral–derivative (PID) and fuzzy PID controllers, liquid metal-based sensing, thermoelectric cooling (TECs), and evaporation or integrated heating elements for precise thermal output management. Emerging fabrication technologies, such as additive manufacturing, enable the direct integration of heating elements and sensors within microchips, improving thermal efficiency and device compactness. Advanced materials, including carbon nanotubes infused with gallium and temperature-sensitive quantum dots, offer innovative, non-contact thermal monitoring capabilities. Furthermore, artificial intelligence-driven feedback systems present opportunities for adaptive, real-time thermal optimization. By consolidating these strategies, this review highlights pathways to develop more dependable, efficient, and application-ready microfluidic devices, with implications for diagnostics, research, and other practical uses. Full article

We theoretically studied the control of the extraction of anti-Stokes photoluminescence using photonic crystal (PhC) nanocavities. Our fabricated (erbium,oxygen)-codoped GaAs PhC nanocavity showed a positive feedback gain of heating through the excitation of the GaAs host, which suggests the possibility of higher laser-cooling efficiencies at lower temperatures in such systems. Based on this result, we constructed a theoretical framework of laser cooling in PhC nanocavities. The predicted laser cooling efficiency of a PhC nanocavity is six to eight times higher than that of the corresponding bulk system, and we predict that more than 24% can be achieved at 100 K using holmium-doped materials. Full article

This paper presents the dynamic behavior of a nonlinear bioreactor model designed for fermentation processes, subject to temperature variations throughout the day. Ethanol production is presented by analyzing the fermenter’s temperature, which is controlled by the flow of the cooling fluid (water) that passes through the fermenter jacket. To optimize ethanol production during a period, a control design considering the optimal linear feedback control (OLFC) designed for nonlinear systems is introduced to control the flow of the cooling fluid of the bioreactor. Numerical and computational simulations demonstrated that the proposed control is efficient in maintaining the temperature at the desired levels and is resistant to parametric variations. With the results obtained from the optimal control (OLFC) and state-dependent Riccati equation (SDRE) control, a neuro-fuzzy control system is obtained, thus enabling the application of the proposed control in other bioreactor systems with similar dynamics. Full article

Concrete quality on construction sites depends on maintaining certain workability during transportation. However, traditional slump testing is manual and cannot assess concrete in transit. This study presents a cyber-physical system (CPS) integrating IoT sensors with machine learning models to estimate concrete workability in real time during delivery. The proposed approach first correlates traditional slump test parameters with sensor measurements, allowing for automated replication of established workability evaluation. The CPS continuously captures IoT sensor data, such as drum rotation, vibration, internal pressure, and temperature, processes these data in real time, and infers workability before unloading. The developed CPS was validated in a real-world case study, achieving high workability prediction accuracy with an average error of approximately 0.9 cm and timely, automated feedback of below 200 ms. These results enable continuous in-transit monitoring of concrete workability and lay a practical foundation for data-driven operational improvements in construction logistics. Full article

The construction industry faces significant challenges due to the physically demanding and hazardous nature of tasks such as manual filling of expansion joints with mastic. Automating mastic filling presents additional difficulties due to the variability of mastic density with temperature, which creates a constantly changing environment that requires adaptive control strategies to ensure consistent application quality. This pilot study focuses on testing a new human–robot collaborative approach for automating the mastic application in concrete expansion joints. The system learns the task from demonstrations performed by expert construction operators teleoperating the robot. This study evaluates the usability, efficiency, and adoption of robotic assistance in joint-filling tasks compared to traditional manual methods. The study analyzes execution time and joint quality measurements, psychophysiological signal analysis, and post-task user feedback. This multi-source approach enables a comprehensive assessment of task performance and both objective and subjective evaluations of technology acceptance. The findings underscore the effectiveness of automated systems in improving safety and productivity on construction sites, while also identifying key areas for technological improvement. Full article

In loop-powered 4–20 mA transmitter systems, sensors like temperature, pressure, flow, and gas sensors are chosen based on specific application requirements. These systems are widely adopted in high-precision measurement scenarios, including industrial automation, process control, and environmental monitoring. The transmitter requires a high-performance analog front end (AFE) for precise amplification and signal conditioning. This paper presents a low-noise instrumentation amplifier (IA) for high-precision transmitter front ends, featuring a Successive Approximation Register (SAR)-assisted offset calibration architecture. The proposed structure integrates a chopper current-feedback instrumentation amplifier (CFIA) with an automatic offset calibration loop (AOCL), significantly suppressing internal offset errors and enabling high-accuracy signal acquisition under stringent power and environmental temperature constraints. The designed amplifier provides four selectable gain settings, covering a range from ×32 to ×256. Fabricated in a 0.18 μm CMOS process, the CFIA operates at a 1.8 V supply voltage, consumes a static current of 182 μA, and achieves an input-referred noise as low as 20.28 nV/√Hz at 1 kHz, with a common-mode rejection ratio (CMRR) up to 122 dB and a power-supply rejection ratio (PSRR) up to 117 dB. Experimental results demonstrate that the proposed amplifier exhibits excellent performance in terms of input-referred noise, offset voltage, PSRR, and CMRR, making it well-suited for front-end detection in field instruments that require direct interfacing with measured media. Full article

This study conducts a simulation-based approach to improve microwave (MW) convective drying using a temperature-responsive pulse ratio (TRPR) method. Traditional fixed-time pulse ratio (TimePR) techniques often result in uneven heating and reduced product quality due to uncontrolled temperature spikes. To address this, a physics-based model was developed using COMSOL Multiphysics 6.3, executed on a high-performance computing (HPC) platform. The TRPR algorithm dynamically adjusts MW ON/OFF cycles based on internal temperature feedback, maintaining the maximum point temperature below a critical threshold of 75 °C. The model geometry, food materials (apple) properties, and boundary conditions were defined to reflect realistic drying scenarios. Simulation results show that TRPR significantly improves temperature and moisture uniformity across the sample. The TRPR method showed superior thermal stability over time-based regulation, maintaining a lower maximum COV of 0.026 compared to 0.045. These values are also well below the COV range of 0.05–0.26 reported in recent studies. Moreover, the TRPR system maintained a constant microwave energy efficiency of 40.7% across all power levels, outperforming the time-based system, which showed lower and slightly declining efficiency from 36.18% to 36.29%, along with higher energy consumption without proportional thermal or moisture removal benefits. These findings highlight the potential of the temperature-responsive pulse ratio (TRPR) method to enhance drying performance, reduce energy consumption, and improve product quality in microwave-assisted food processing. This approach presents a scalable and adaptable solution for future integration into intelligent drying systems. Full article

Scramjet operation requires a comprehensive understanding of the internal flowfield, encompassing fuel–air mixing and combustion. This study investigates transient flow and flame development within a HIFiRE-2 scramjet engine combustor, which features two opposing cavities and dual sets of fuel injectors—the upstream (primary) and downstream (secondary) injectors. These cavities function as flameholders, creating circulating flows with elevated temperatures and pressures. Shock waves form both ahead of fuel plumes and at the diverging and converging sections of the flowpath. Special attention is given to the interactions among these shock waves and the shear layers along the supersonic core flow as the system progresses towards a quasi-steady state. Driven by increased backpressure, bow shocks and disturbances induced by the normal, secondary fuel injection and the inclined, primary fuel injection move upstream, amplifying the cavity pressure. These shocks generate adverse pressure gradients, causing near-wall flow separation adjacent to both injector sets, which enhances the penetration and dispersion of fuel plumes. Once a quasi-steady state is achieved, a feedback loop is established between dynamic wave motions and combustion processes, resulting in sustained entrainment of reactive mixtures into the cavities. This mechanism facilitates stable combustion in the cavities and near-wall separation zones. Full article

This study presents the development of an innovative multifunctional cup holder designed to enhance safety, usability, and sustainability. Addressing common issues such as accidental spills, heat retention, and structural stability, the proposed design incorporates adjustable fixation and heating functionalities. The research applies a systematic design approach, applying the Theory of Inventive Problem Solving (TRIZ) methodology to resolve design contradictions and enhance product functionality. By integrating human factors considerations and universal design principles, the cup holder aims to improve user experience and accessibility. The design features a vacuum-based adjustable fixation system to prevent tipping, a controlled heating mechanism to maintain beverage temperature, and a shock-absorbing structure for enhanced durability. To evaluate whether the final design meets user expectations, a SERVQUAL questionnaire was used to collect user feedback, which was then analyzed using the Importance–Performance Analysis combined with the Kano model (IPA-Kano model). The results revealed an overall importance score of 4.347 and a satisfaction score of 3.943. Key strengths identified include reliable shock resistance, effective fixation, and ease of operation, while areas such as brand reputation and temperature control precision were found to require improvement due to their high importance but low performance. These insights confirm that the proposed design effectively enhances stability, thermal performance, and user convenience, while aligning with users’ expectations. By addressing critical functional and safety needs, this research advances the development of practical, user-centered innovations in everyday product design. Full article