Search Results (178)

A ring-oscillator based voltage-controlled oscillator (VCO) architecture with reduced frequency drift across temperature and process variations is presented in this paper. The frequency stability is achieved through two dedicated compensation techniques: a temperature compensation circuit that generates a proportional-to-absolute-temperature (PTAT) current to mitigate frequency shifts due to temperature changes, and a process compensation circuit that dynamically adjusts the frequency based on detected process corners. The proposed design is implemented in a 22 nm CMOS technology with a 0.8 V supply voltage and targets a nominal oscillation frequency of 2.5 GHz. The post-layout simulation results demonstrate a significant improvement in frequency stability, reducing temperature-induced frequency drift from 23.9% to a range of 5.4% over the −40 °C to 125 °C temperature range for the typical corner. Combining temperature and process compensation, the frequency drift is improved from 47.3% to better than 7.2%. The VCO also achieves a phase noise value about −80 dBc/Hz at a 1 MHz offset with an average power consumption of 380 µW, including the tuning mechanism and the compensation circuits. Full article

This paper proposes a second-order low-pass Butterworth multiple-feedback (MFB) filter with a reconfigurable bandwidth and gain, implemented in a 28 nm CMOS. The filter supports independent tuning of the bandwidth from 10 MHz to 100 MHz and the gain from 0 dB to 19 dB, effectively addressing the challenge of a tightly coupled gain and quality factor in traditional MFB designs. Notably, compared to the widely adopted Tow–Thomas structure, the proposed filter achieves second-order filtering and the same degree of flexibility using only a single operational amplifier (OPA), significantly reducing both the power consumption and area. Additionally, an RC tuning circuit is employed to reduce fluctuations in the RC time constant under process, voltage, and temperature (PVT) variations. To meet the requirements for high linearity and low power consumption in broadband applications, a three-stage push–pull OPA with current re-use feedforward and an RC Miller compensation technique is proposed. With the current re-use feedforward, the OPA’s loop gain at 100 MHz is significantly enhanced from 22.34 dB to 28.75 dB, achieving a 2.14 GHz unity-gain bandwidth. Using this OPA, the filter achieves a 48.2 dBm in-band (IB) OIP3, a 53.4 dBm out-of-band (OOB) OIP3, and a figure of merit (FoM) of 185.5 dBJ⁻¹ at a100 MHz bandwidth while consuming only 3.6 mW from a 1.8 V supply. Full article

The low water solubility of sulfamethazine (SMT) limits its clinical efficacy, making it crucial to study techniques such as cosolvency to optimize pharmaceutical formulations. This study aimed to thermodynamically evaluate the solubility of SMT in {acetonitrile (MeCN) + ethanol (EtOH)} cosolvent mixtures over a temperature range of 278.15 to 318.15 K in order to understand the molecular interactions that govern this process. SMT solubility in the mixtures was measured using a flask-shaking method. The solid phases were analyzed using differential scanning calorimetry (DSC) to rule out polymorphisms. Using the Gibbs–van’t Hoff–Krug model, we calculated the apparent thermodynamic functions of the solution and mixture from the obtained data. The results showed that solubility increased almost linearly with MeCN fraction and temperature, indicating that MeCN is a more efficient solvent and that the process is endothermic. Thermodynamic analysis revealed that dissolution is an endothermic process with favorable entropy for all compositions. The higher solubility in MeCN is attributed to the lower energetic cost required to form the solute cavity compared to the high energy needed to disrupt the hydrogen bond network of ethanol. This behavior can be explained by an enthalpy–entropy compensation phenomenon. This phenomenon provides an essential physicochemical basis for designing pharmaceutical processes. Full article

This paper presents a novel technique for thermally compensating the power output of a DC-DC converter that supplies automotive lighting/signaling systems with multiple LED branches. The method ensures stable bias voltage for the current drivers controlling each branch, maintaining consistent power consumption across a wide temperature range. This issue has been minimally addressed in existing literature, providing few solutions which are too complex for industrial production. The approach proposed is simple and involves incorporating a temperature-sensitive thermistor into the DC-DC converter’s control loop, enabling the output voltage to adjust with ambient temperature. Different control loop configurations are explored, demonstrating that a simple resistor-thermistor network can approximate the desired voltage response under diverse thermal conditions. The power dissipated in the current drivers is kept within a controlled range, improving system efficiency and reducing heat loss. Additionally, it minimizes the need for additional current drivers, lowering the cost of these systems, improving battery life of the DC-DC converter, and decreasing CO₂ emissions. For the case studies analyzed, an optimized configuration with appropriate resistor values and thermistor models achieves a 75% relative reduction in power dissipation by the current driver and a 50% improvement in the relative efficiency of the LED branch system. Full article

Thermogravimetric analysis (TGA) is a key technique for evaluating the kinetics and thermodynamics of thermal degradation, providing essential data for material assessment and system design. When coupled with Fourier-transform infrared (FT-IR) spectroscopy or mass spectroscopy (MS), it enables the identification of evolved gases and correlates mass loss with specific chemical species, offering detailed insight into decomposition mechanisms. In this study, TGA was coupled with FT-IR and MS to investigate the thermal degradation behavior of Bakelite, with the aim of evaluating its kinetic and thermodynamic parameters under non-isothermal conditions, identifying evolved volatile compounds, and elucidating the degradation process. The results showed that higher heating rates led to increased decomposition temperatures and broader dTG peaks due to thermal lag effects. The degradation proceeded in multiple stages between 220 °C and 860 °C, ultimately yielding a carbonaceous residue. The activation energy increased with conversion, particularly beyond 0.5, indicating a greater energy requirement as degradation progressed. Peak values at conversion degrees of 0.8–0.9 suggested enhanced thermal stability or changes in the dominant reaction mechanism. Detailed kinetic analysis revealed complex decomposition pathways with variable activation energies and a pronounced kinetic compensation effect. Thermodynamic analysis confirmed the endothermic nature of the process, with increasing energy demand and non-spontaneous degradation of the resulting char. TGA/FT-IR and TGA/MS analyses identified the release of several compounds, including CO₂, water, formaldehyde, and phenolic derivatives, at distinct stages. This comprehensive understanding of Bakelite’s thermal behavior supports its optimization for high-temperature applications, enhances material reliability and safety, and contributes to sustainable processing and recycling strategies. Full article

Resistive angle sensors are widely used due to their simple signal conditioning circuits and high cost-effectiveness. This paper presents a resistive angle sensor based on a rotary potentiometer, designed to offer a measurement range of 180° for low-cost angle measurement in industrial automation and electromagnetic interference (EMI)-sensitive applications. The sensor features a specially designed signal conditioning circuit and mechanical housing. Experimental results show that it exhibits excellent linearity and temperature stability over a wide temperature range of −20 °C to 60 °C, with a zero-temperature drift of approximately 0.004°/°C. For the nonlinearity and hysteresis caused by unavoidable friction and manufacturing tolerances between the transmission mechanism and rotary potentiometer, an adaptive linear neuron (ADALINE) technique based on the α-least mean square (α-LMS) algorithm was implemented for software compensation. The results show that the percentage nonlinearity error was reduced from the original 4.413% to 0.182%, and the percentage hysteresis error was decreased from the original 4.061% to 0.404%. The research results of this paper offer valuable insight for high-precision resistive angle sensors. Full article

In this research, an analysis of the thermomagnetic properties of a nanoscale spin-2 and spin-3/2 system is conducted. This system is modeled with as a quasi-spherical Ising-type nanoparticle with a diameter of 2 nm, in which atoms with spin-2 and spin-3/2 configured in body-centered cubic (BCC) lattices interact within their relevant nanostructures. To determine the thermomagnetic behaviors of the nanoparticle, numerical simulations using Monte Carlo techniques and thermal bath class algorithms are performed. The results exhibit the effects of exchange couplings ($J_1,J_2^{\prime }$), magnetocrystalline anisotropies ($D_{3/2}^{\prime },D_2^{\prime }$), and external magnetic fields ($h^{\prime }$) on the finite-temperature phase diagrams of magnetization ($M_T$), magnetic susceptibility (${\chi }_T$), and thermal energy ($k_B{T}^{\prime }$). The influences of the exchange, anisotropic, and external field parameters are clearly reflected in the compensation, hysteretic, and pseudocritical phenomena presented by the quasi-spherical nanoparticle. When the parameter reflecting ferromagnetic second-neighbor exchanges in the nanosphere ($J_2^{\prime }$) increases, for a given value of the external magnetic field, the compensation ($T_{comp}$) and pseudocritical ($T_{pc}$) temperatures increase. Similarly, in the ranges $0<J_2^{\prime }⩽4.5$ and $-15⩽h^{\prime }⩽15$ at a specific temperature, an increase in $J_2^{\prime }$ results in the appearance of exchange anisotropies (exchange bias) and and increased hysteresis loop areas in the nanomodel. Full article

Accurate estimation of the state of charge (SOC) is important for the effective management and utilization of lithium-ion battery packs. While advanced estimation methods present in scientific literature commonly rely on detailed cell parameters and laboratory-controlled conditions, practical engineering applications often require solutions applicable to battery packs with unknown or limited internal characteristics. In this context, this study compares three different SOC estimation strategies—voltage-based, coulomb counting, and charge balance methods—implemented in an independent telemetry module (TIO) and their performance against a commercial battery management system (Orion BMS2). Experimental results demonstrate that the voltage-based method provides insufficient accuracy due to its inherent sensitivity to voltage thresholds and internal resistance under load conditions. Conversely, coulomb counting, with periodic recalibration through full charging cycles, showed significantly improved accuracy, closely matching the Orion BMS2 outputs when properly initialized. The results confirm the viability of coulomb counting as a pragmatic approach for battery packs lacking detailed cell data. Future research should address reducing dependency on periodic full-charge resets by incorporating adaptive estimation techniques, such as Kalman filtering or observers, and leveraging open-circuit voltage measurements and temperature compensation to further enhance accuracy while maintaining the simplicity and external applicability of the monitoring system. Full article

In the process of collecting operational data for the performance analysis of water-cooled centrifugal chillers, missing values are inevitable due to various factors such as sensor errors, data transmission failures, and failure of the measurement system. When a substantial amount of missing data is present, the reliability of data analysis decreases, leading to potential distortions in the results. To address this issue, it is necessary to either minimize missing occurrences by utilizing high-precision measurement equipment or apply reliable imputation techniques to compensate for missing values. This study focuses on two water-cooled turbo chillers installed in Tower A, Seoul, collecting a total of 118,464 data points over 3 years and 4 months. The dataset includes chilled water inlet and outlet temperatures ($T_1$ and $T_2$) and flow rate (${\dot{V}}_1$) and cooling water inlet and outlet temperatures ($T_3$ and $T_4$) and flow rate (${\dot{V}}_3$), as well as chiller power consumption (${\dot{W}}_c$). To evaluate the performance of various imputation techniques, we introduced missing values at a rate of 10–30% under the assumption of a missing-at-random (MAR) mechanism. Seven different imputation methods—mean, median, linear interpolation, multiple imputation, simple random imputation, k-nearest neighbors (KNN), and the dynamically clustered KNN (DC-KNN)—were applied, and their imputation performance was validated using MAPE and CVRMSE metrics. The DC-KNN method, developed in this study, improves upon conventional KNN imputation by integrating clustering and dynamic weighting mechanisms. The results indicate that DC-KNN achieved the highest predictive performance, with MAPE ranging from 9.74% to 10.30% and CVRMSE ranging from 12.19% to 13.43%. Finally, for the missing data recorded in July 2023, we applied the most effective DC-KNN method to generate imputed values that reflect the characteristics of the studied site, which employs an ice thermal energy storage system. Full article

The critical consequence of climate change resulting from global warming is the increase in temperature. In combined cycle power plants (CCPPs), the Electric Power Output (PE) is affected by changes in both Ambient Temperature (AT) and Sea Surface Temperature (SST), particularly in plants utilizing seawater cooling systems. As AT increases, air density decreases, leading to a reduction in the mass of air absorbed by the gas turbine. This change alters the fuel–air mixture in the combustion chamber, resulting in decreased turbine power. Similarly, as SST increases, cooling efficiency declines, causing a loss of vacuum in the condenser. A lower vacuum reduces the steam expansion ratio, thereby decreasing the Steam Turbine Power Output. In this study, the effects of increases in these two parameters (AT and SST) due to global warming on the PE of CCPPs are investigated using various regression analysis techniques, Artificial Neural Networks (ANNs) and a hybrid model. The target variables are condenser vacuum (V), Steam Turbine Power Output (ST Power Output), and PE. The relationship of V with three input variables—SST, AT, and ST Power Output—was examined. ST Power Output was analyzed with four input variables: V, SST, AT, and relative humidity (RH). PE was analyzed with five input variables: V, SST, AT, RH, and atmospheric pressure (AP) using regression methods on an hourly basis. These models were compared based on the Coefficient of Determination (R²), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Root Mean Square Error (RMSE). The best results for V, ST Power Output, and PE were obtained using the hybrid (LightGBM + DNN) model, with MAE values of 0.00051, 1.0490, and 2.1942, respectively. As a result, a 1 °C increase in AT leads to a decrease of 4.04681 MWh in the total electricity production of the plant. Furthermore, it was determined that a 1 °C increase in SST leads to a vacuum loss of up to 0.001836 bar_a. Due to this vacuum loss, the steam turbine experiences a power loss of 0.6426 MWh. Considering other associated losses (such as generator efficiency loss due to cooling), the decreases in ST Power Output and PE are calculated as 0.7269 MWh and 0.7642 MWh, respectively. Consequently, the combined effect of a 1 °C increase in both AT and SST results in a 4.8110 MWh production loss in the CCPP. As a result of a 1 °C increase in both AT and SST due to global warming, if the lost energy is to be compensated by an average-efficiency natural gas power plant, an imported coal power plant, or a lignite power plant, then an additional 610 tCO₂e, 11,184 tCO₂e, and 19,913 tCO₂e of greenhouse gases, respectively, would be released into the atmosphere. Full article

In this paper, a double-mode self-calibration tension system is proposed, which adopts the conversion of hydraulic meter tension and the monitoring of standard force sensors. According to the material characteristics of the jack and the viscosity and temperature characteristics of the hydraulic oil, the differential model of heat conduction in the hydraulic cylinder and the mathematical model of oil film friction heat generation are established, and the internal thermodynamic characteristics of the jack are theoretically analyzed, which provides theoretical support for the temperature compensation of the hydraulic oil pressure gauge of the jack. A simulation analysis was conducted on the thermodynamic characteristics of the hydraulic jack, and the distribution patterns of the temperature field, thermal stress field, and thermal strain field inside the hydraulic cylinder during normal operation were determined by measuring the temperature changes in five different parts of the jack at different times (t = 200 s, 2600 s, 5000 s, 7400 s, and 10,000 s). For the issue of heat generation due to oil film friction in the hydraulic jack, a simulation calculation model is developed by integrating Computational Fluid Dynamics (CFD) techniques with dynamic grid and slip grid methods. By simulating and analyzing frictional heating under conditions where the inlet pressures are 0.1 MPa, 0.3 MPa, 0.5 MPa, 0.7 MPa, and 0.9 MPa, respectively, we can obtain the temperature distribution on the jack, determine the frictional resistance, and subsequently conduct a theoretical analysis of the simulation results. Using the high-precision standard force sensor after data processing and the hydraulic oil gauge after temperature compensation, the online self-calibration of the tensioning system is carried out, and the regression equation of the tensioning system under different oil temperatures is obtained. The double-mode self-calibration tensioning system with temperature compensation is used to verify the compensation accuracy of the proposed double-mode self-calibration tensioning system. Full article

This paper focuses on the application of fractional calculus techniques in the identification and control of multivariable (multiple input—multiple output) systems (MIMO). By considering a previously reported experimental set-up similar to a greenhouse, this study proposes the open-loop identification of fractional order transfer functions relating to the controlled and manipulated variables, which were validated by experimental data. Afterward, the theoretical analysis of Fractional-order Proportional and Integral (FOPI) closed-loop control for this MIMO system was carried out. An important aspect concerns the use of Particle Swarm Optimization (PSO) metaheuristic algorithm for optimization tasks, both in parameter estimation and controller tuning. Moreover, comparisons with integer order models and controllers (IOPID-IMC) were performed. The results demonstrate the superior performance and robustness of the FOPI-PSO fractional control, which achieves up to 79.6% reduction in ITAE and 72.1% reduction in ITSE criteria. Without the need for explicit decouplers, the decentralized FOPI-PSO control structure demonstrated effective handling of interactions between the temperature and humidity control loops, simplifying the control design while maintaining performance. The fractional-order controllers exhibited robustness to measurement noise, as evidenced by stable and precise control responses in the presence of experimental uncertainties. Additionally, the optimized tuning of FOPI controllers implicitly compensated for disturbances and setpoint changes without requiring additional feedforward mechanisms. This study contributes to a better understanding of fractional calculus applications in designing FO–MIMO systems and provides a practical framework for addressing the identified gaps in the field. Full article

Understanding cellular interaction with nanomaterials represents a subject of great interest for the validation of new diagnostic and therapeutic tools. A full characterization of a designed product includes the evaluation of its impact on specific biological systems, including the study of cell behavior as a response to that particular interaction. Copper and copper-based nanoparticles (CuO NPs) have emerged as valuable building blocks for various biomedical applications such as antibacterial and disinfecting agents for infectious diseases, and the evaluation of the metabolism of food, including the iron required for proteins and enzymes or as drug delivery systems in cancer therapy. In this study, the biological impact of manganese-doped crystalline copper oxide (CuO:Mn) nano-platelets on human normal BJ fibroblasts and human A375 skin melanoma was assessed. The particles were synthesized at room temperature via the hydrothermal method. A complete physicochemical characterization of the materials was performed by employing various techniques including X-ray diffraction, electron microscopy, X-Ray photoelectron spectroscopy, and dynamic light scattering. Morphological investigations revealed a flat structure with nearly straight edges, with sizes spanning in the nanometer range. XRD analysis confirmed the formation of the CuO phase with good crystallinity, while XPS provided insights into the Mn doping. The findings indicate that nano-platelets interact with cells actively by mediating essential molecular processes. The exogenous manganese triggers increased MnSOD production in mitochondria, compensating ROS produced by external stress factors (Cu²⁺ ions), and mimics the endogenous SODs production, which compensates internal ROS production as it normally results from cell biochemistry. The effect is differentiated in normal cells compared to malignant cells and deserves investigation. Full article

Non-destructive testing (NDT) plays a crucial role in ensuring the structural integrity and safety of industrial facilities and components. Long pulse thermography (LPT), a form of active thermographic testing (ATT), has gained attention for its ability to detect subsurface defects efficiently. However, non-uniform thermal excitation and environmental noise often degrade the accuracy of defect detection. This study proposes an advanced thermographic inspection technique incorporating a halogen array (HA) lamp and a compensation methodology to enhance the reliability of defect detection. Two compensation methods, namely absolute temperature compensation (ATC) and temperature rate compensation (TRC), were developed to correct non-uniform thermal loads and improve the defect contrast. Experimental validation was conducted on A-type and B-type mock-up specimens with artificial subsurface defects (10–90% depth). The results demonstrated a significant enhancement in the signal-to-noise ratio (SNR), reaching up to a 42 dB improvement in severe defects. Furthermore, a quantitative evaluation method was proposed using SNR-based defect depth estimation models, improving the accuracy of defect sizing. This approach eliminates the need for complex amplitude and phase transformations, enabling direct defect assessment from temperature thermograms. Full article

The hydraulic support is one of the most crucial pieces of equipment at the working face. To achieve the intelligentization of the attitude-monitoring system, we have designed and developed a Fiber Bragg Grating (FBG) inclinometer for the hydraulic support. This innovation offers a brand-new monitoring tool and approach for measuring the attitude angle of the hydraulic support. The FBG inclinometer for the hydraulic support integrates passive grating sensing technology with an inclination force element. It not only fulfills the inclination measurement function but also employs passive sensing technology, rendering it safer and more reliable compared to electromagnetic inclinometers. First, we delved into the sensing principle of the grating based on its structure, and investigated its sensing characteristics under uniform axial stress and temperature variations. We analyzed the strain–temperature cross-sensitivity issue and applied a temperature compensation technique. Second, we carried out a novel structural design and proposed two design alternatives: the cantilever beam type was selected after a comprehensive comparison. Subsequently, we deduced the corresponding theoretical formulas and ultimately adopted the temperature compensation method using an unstressed reference grating. Finally, on-site verification was conducted on the hydraulic support in the general mining face of Delong Mine, and the FBG inclinometer successfully passed the test. Finally, an actual test was carried out at the Delong Coal Mine site, and the subsequent use yielded quite satisfactory results. An analysis of the data collected on-site by the FBG inclinometer for the hydraulic support revealed that the newly developed FBG inclinometer for the hydraulic support can be effectively applied in the field of intelligent monitoring in underground coal mines. The monitoring data can serve as a reliable data foundation for assessing the operating attitude of the hydraulic support. This indicates that the FBG inclinometer is highly suitable for wide-scale industrial applications. Full article