Presence Of Temperature Variations Research Articles

Effects of chemical reactions in the presence of temperature variations and isothermal mass diffusion over an inclined plate

A detailed study of the erratic circulation around an unbounded inclined plate under fluctuating temperature and isothermal mass dispersion was carried out with a chemical reaction. This work concentrated on the harmonic inclination of the plate in its plane, and the accurate solution of the non-dimensional governing formulations was made possible by the Laplace transform technique. To evaluate their impact on different profiles, the investigation examined a variety of physical factors, including phase inclination, chemical response variable, Schmidt number, thermal Grashof number, mass Grashof number, and duration. Notably, the speed per second increased with decreasing phase angle. Furthermore, a decrease in either the thermal radiation variable or the chemical response variable induced an increase in velocity.

Effects of external field and potential on non-relativistic quantum particles in disclinations background

In this work, we investigate the behavior of non-relativistic quantum particles immersed in a cosmic string space-time background. Our study involves the examination of these particles as they interact with a range of influences, including potential, magnetic, and quantum flux fields. We employ analytical methods to solve the associated wave equation, leading to the derivation of eigenvalue solutions for this quantum system. Subsequently, we leverage these eigenvalue solutions to scrutinize several potential models. For each model, we present and engage in a thorough discussion of the corresponding eigenvalue solutions. In an extension of our investigation, we explore the thermodynamic and magnetic properties of the quantum system when it is exposed to non-zero temperature conditions, denoted by [Formula: see text]. Our analysis encompasses the calculation of essential parameters such as the partition function for the system and other pertinent functions. Following these calculations, we meticulously examine and interpret the outcomes, shedding light on the system’s behavior and characteristics in the presence of temperature variations. Furthermore, we calculate entropic information to investigate the location of particles in the system.

Composite encoder–decoder network for rapid bridge damage assessment using long-term monitoring acceleration data

In recent years, the deployment of structural health monitoring (SHM) systems has become paramount for safeguarding critical infrastructures. Notwithstanding, the development of an unsupervised deep learning framework capable of learning from long-term sensor data remains a critical challenge, particularly in accurately assessing the exact damage location. This study addresses this gap by proposing a novel approach for rapid bridge damage assessment. The proposed method employed a deep overcomplete encoder–decoder network (DOEDN) to reconstruct the acceleration data acquired from each sensor node on the bridge. The reconstruction losses generated by the DOEDN framework are then used as damage-sensitive features. Additionally, a damage indicator based on Gaussian processes is introduced to assess the damage location and evaluate its severity. The performance and sensitivity of the proposed DOEDN framework are evaluated through long-term monitoring acceleration data from a numerical highway bridge model and the well-known full-scale Z24 bridge. Furthermore, comparative assessments against the regular deep undercomplete encoder–decoder network are conducted using metrics including mean absolute error, coefficient of determination (R2), and mean intersection over union. The results show that the proposed DOEDN framework can reasonably assess the damage location and evaluate its severity across various structural scenarios in the bridge, even in the presence of temperature variations, thus providing a practical and effective solution for bridge health monitoring.

Enhanced stability of gold nanoparticles capped with double hydrophilic block copolymers synthesized by eATRP

AbstractIn this study, the gold nanoparticles (Au NPs) are capped with a novel, well‐defined double hydrophilic block copolymer, poly (ethylene glycols)‐block‐poly(mono‐2‐(methacryloyloxy) ethyl succinate) (PEG‐b‐PSEMA). The PEG‐b‐PSEMA, with long side chains and relatively narrow dispersity index, is successfully prepared by aqueous electrochemically mediated atom transfer radical polymerization using a PEG‐Br macroinitiator (Mn≈2000 g mol−1). By simply mixing PEG‐b‐PSEMA and Au precursor before adding reductants, coulombic interactions occur between the Au precursor and the carboxylate group of the PSEMA, as a result dense Au NPs are formed. This enables the Au NPs to remain dispersed even in the presence of temperature variations, pH adjustments, and incubation in organic solvents. Au NPs were endowed by PEG‐b‐PSEMA with more remarkable catalytic activity in organic solvents of 4‐nitrophenol into 4‐aminophenol than by sodium citrate (Au@citrate) and MeO‐PEG‐OH (Au@PEG). In addition, PEG‐b‐PSEMA‐stabilized Au NPs (Au@PEG‐b‐PSEMA) were also tested for the dye degradation property against Rhodamine‐B in only pH 10 basic solution, and over 99% of dye degradation can be achieved in 9 min. PEG‐b‐PSEMA induces coulombic interactions with Au NPs, providing outstanding stability for catalytic applications in organic or specific acidic‐base environments.

Ultrasonic Testing of Mechanical Changes in a Water-Filled Pipe with Multi-Mode and Broadband Signals and Two-Level Compensation.

Ultrasonic testing (UT) has been widely used for the Nondestructive Evaluation (NDE) of pipes due to its many favorable characteristics. However, one of the main challenges in the general use of UT for real-world pipelines is the sensitivity of this method to environmental and operational condition changes. This paper proposes a new UT method with enhanced compensation for environmental effects and operational condition changes. In particular, the effectiveness of the new method is tested in the presence of temperature variations, and changes in water flow rate inside a stainless-steel pipe. The proposed UT method uses multi-mode and broadband guided ultrasonic waves in the pipe walls, excited and received by single-element ultrasonic sensors that are spatially separated, forming a measurement zone between any pair of such transmit and receive sensors. Amplitude changes, time shifts, and frequency content variations in the ultrasonic signal due to temperature changes and water flow are evaluated and compensated for reliable UT of mechanical changes in the pipe. It is observed that spurious effects of water flow on ultrasonic response, if not properly compensated, can dominate over effects due to actual mechanical changes, but such liquid-boundary effects can be compensated effectively by the proposed time- and frequency-filtering method.

Energy Harvesting from Thermal Variation with Phase-Change Materials

Phase-change materials with temperature-dependent thermal conductivity have drawn lots of attention recently. They have exhibited promising potentials in devices such as the thermal diode, thermal memristor, etc. Here we investigate the heat exchange between two reservoirs through a bare phase-change material. In the presence of temperature variation in one of the reservoirs, we find a unidirectional thermal flux between those two reservoirs though they share the same average temperature, i.e., no temperature bias. By mapping such a system to the heat exchange between two reservoirs through a regular material with a constant thermal conductivity, we obtain an effective temperature difference ${T}_{\mathrm{eff}}$, which should present to maintain the unidirectional thermal flux. We then provide a semianalytical formula for ${T}_{\mathrm{eff}}$, which works well over an extensive parameter range. The parameter dependence of ${T}_{\mathrm{eff}}$ and the temperature dependence of the thermal capacity are then studied in detail. Our work thus provides a useful tool for calibration of heat conduction within phase-change materials and leads to potential applications related to energy extraction from the thermal variation of the environment.

Analysis of the Impact of Sustained Load and Temperature on the Performance of the Electromechanical Impedance Technique through Multilevel Machine Learning and FBG Sensors.

The electro-mechanical impedance (EMI) technique has been applied successfully to detect minor damage in engineering structures including reinforced concrete (RC). However, in the presence of temperature variations, it can cause false alarms in structural health monitoring (SHM) applications. This paper has developed an innovative approach that integrates the EMI methodology with multilevel hierarchical machine learning techniques and the use of fiber Bragg grating (FBG) temperature and strain sensors to evaluate the mechanical performance of RC beams strengthened with near surface mounted (NSM)-fiber reinforced polymer (FRP) under sustained load and varied temperatures. This problem is a real challenge since the bond behavior at the concrete–FRP interface plays a key role in the performance of this type of structure, and additionally, its failure occurs in a brittle and sudden way. The method was validated in a specimen tested over a period of 1.5 years under different conditions of sustained load and temperature. The analysis of the experimental results in an especially complex problem with the proposed approach demonstrated its effectiveness as an SHM method in a combined EMI–FBG framework.

Optimal Control and Temperature Variations of Malaria Transmission Dynamics

Malaria is a Plasmodium parasitic disease transmitted by infected female Anopheles mosquitoes. Climatic factors, such as temperature, humidity, rainfall, and wind, have significant effects on the incidence of most vector-borne diseases, including malaria. The mosquito behavior, life cycle, and overall fitness are affected by these climatic factors. This paper presents the results obtained from investigating the optimal control strategies for malaria in the presence of temperature variation using a temperature-dependent malaria model. The study further identified the temperature ranges in four different geographical regions of sub-Saharan Africa, suitable for mosquitoes. The optimal control strategies in the temperature suitable ranges suggest, on average, a high usage of both larvicides and adulticides followed by a moderate usage of personal protection such as bednet. The average optimal bednet usage mimics the solution profile of the mosquitoes as the mosquitoes respond to changes in temperature. Following the results from the optimal control, this study also investigates using a temperature-dependent model with insecticide-sensitive and insecticide-resistant mosquitoes the impact of insecticide-resistant mosquitoes on disease burden when temperature varies. The results obtained indicate that optimal bednet usage on average is higher when insecticide-resistant mosquitoes are present. Besides, the average bednet usage increases as temperature increases to the optimal temperature suitable for mosquitoes, and it decreases after that, a pattern similar to earlier results involving insecticide-sensitive mosquitoes. Thus, personal protection, particularly the use of bednets, should be encouraged not only at low temperatures but particularly at high temperatures when individuals avoid the use of bednets. Furthermore, control and reduction of malaria may be possible even when mosquitoes develop resistance to insecticides.

Model-based statistical guided wave damage detection for an aluminum plate

Accurate decision-making requires understanding the factors that influence those decisions. In guided wave structural health monitoring, the first aim is to detect the presence of damage. This decision is based on the assumption that it is possible to discriminate between undamaged and damaged states. Sensing systems collect data to construct damage statistics, that is, numerical representations of how the state of the structure has changed over time. These damage statistics are designed to be sensitive to damage signatures in the data. However, environmental and operating conditions, such as the presence of temperature variations, perturb damage statistics and weaken decision-making. Temperature compensation strategies applied to reduce these perturbations are imperfect. Qualifying the performance of a temperature compensation strategy to reduce or eliminate the effects of temperature is dependent on the resulting damage statistics. Quality temperature compensation strategies must be able to recover damage statistics and increase damage detection accuracy. This article establishes a framework for evaluating the performance of damage detection methods that use temperature compensation to reduce the effects of environmental and operating conditions. Here, the scale transform and the dynamic time warping method are examined for data with varying temperature and signal-to-noise ratios. Monte Carlo simulations are used to construct probability densities and perform statistical analysis on the resulting damage statistics.

Impacts of Process and Temperature Variations on the Crosstalk Effects in Sub-10 nm Multilayer Graphene Nanoribbon Interconnects

In this study, a comprehensive analysis of the crosstalk in multilayer graphene nanoribbon (MLGNR) interconnects in the presence of process and temperature variations is performed. The variations of the crosstalk delay, crosstalk noise area, and power are investigated in the presence of process and temperature variations for passively shielded five-line MLGNRs carrying ternary signals in 10nm and 7nm technology nodes. Analyses are conducted considering all of the important sources of process variations using comprehensive Monte Carlo simulations. The results indicate that the impacts of the process and temperature variations on the crosstalk effects become more evident with the technology scaling from 10 to 7nm, mainly due to the reduction of the width and spacing of the interconnects. According to the results, the maximum deviation of the crosstalk delay, power consumption, and noise area are 160ps, $0.9{\mu }\text{W}$ and 16V.ps, respectively for 10nm passively shielded MLGNR interconnect in the presence of all sources of process variations. These values are in turn 335ps, $1.3{\mu }\text{W}$ , and 27V.ps in 7nm node. Moreover, the crosstalk effects are evaluated at various temperatures ranging from 200°K to 450°K. The maximum variations for the crosstalk delay and noise area for 10nm MLGNR interconnects are 57ps and 6V.ps at temperatures higher than room temperature and 6ps and 0.5V.ps for temperatures lower than the room temperature. These variations are in turn 118ps, 9V.ps, 12ps and 1V.ps for 7nm MLGNR interconnects. It is also observed that the variations of the resistance of the $500{\mu }\text{m}$ length MLGNR in the presence of temperature variations are on average 3.9 $\text{K}\Omega $ and 8.2 $\text{K}\Omega $ in 10nm and 7nm technologies, respectively.

The annual surface temperature patterns across the Dead Sea as retrieved from thermal images

Satellite images capture a large scene instantaneously, enabling direct comparisons of surface–atmosphere interactions in a static time domain. The annual course of surface temperature of the Dead Sea is investigated using thermal images obtained from Band 10 onboard Landsat 8. Retrieved sea surface temperature varied from around 20 °C in February to ~ 35 °C in July. Retrieved sea surface temperature is commensurate with extensive field measurements, with a root mean square error of 1.25 °C. Satellite images reveal three distinct thermal patterns. The first one is the presence of temperature variations across the open sea which may reflect differences in local meteorology and/or differential mixing with the deeper layers. The second feature is the different temperature skewness patterns between winter and summer months. A slight negative temperature skewness is observed during the period November through February, and a steep positive one during the rest of the year, with large values occurring during summer. These skewness patterns reflect the variations in the annual course of heating and cooling mechanisms occurring in the open sea and along the shallow shorelines. The third distinct feature is the presence of cold finger plumes during the cold months, extending around 4 km inside the open sea and covering an area in excess of 3 km2. The influence of freshwater flux on evaporation from large hypersaline water bodies is investigated using a theoretical formulation derived in this paper. Results show that the effect of freshwater flux on evaporation from hypersaline lakes is a complex process determined by activity and temperature departures. Satellite images provide an excellent surrogate to field observations which are money and labor intensive, time consuming, and very limited in their spatial coverage.

Bridge Real-Time Damage Identification Method Using Inclination and Strain Measurements in the Presence of Temperature Variation

In this paper, a new real-time damage identification method has been presented for bridge structural health monitoring (SHM) considering temperature variation. The method utilizes model-based damage identification that involves three major steps: (1) efficient basis functions—extracted from finite-element (FE) models prior to real-time identification; (2) partial least-squares regression (PLSR) analyses; and (3) the fusion of different types of structural responses into damage indicator. By treating local damages as equivalent vertical loads and then cross-referencing global (inclinations) and local (strain) data, the hidden damage information in bridge structures can be detected and localized in a timely fashion, even in the presence of unknown temperature variation as well as vehicle loads. Inclinations alone cannot reflect local damages, but by fusing inclinations and strains (that represent local damage) into the proposed damage indicator, local damages can be identified. Numerical simulations on a medium-span continuous bridge demonstrate that the proposed method is insensitive to measurement noise and some common modeling errors, revealing the potential of real-time damage identification in bridge SHM applications.

A Learning-Based Thermal-Sensitive Power Optimization Approach for Optical NoCs

Optical networks-on-chip (NoCs) based on silicon photonics have been proposed as emerging on-chip communication architectures for chip multiprocessors with large core counts. However, due to the thermal sensitivity of optical devices used in optical NoCs, on-chip temperature variations cause significant thermal-induced optical power loss, which would counteract the power advantages of optical NoCs. To tackle this problem, in this work, we propose a learning-based thermal-sensitive power optimization approach for mesh- or torus-based optical NoCs in the presence of temperature variations. The key techniques proposed include an initial device-setting and thermal-tuning mechanism that is a device-level optimization technique, and a learning-based thermal-sensitive adaptive routing algorithm that is a network-level optimization technique. Simulation results of an 8x8 mesh-based optical NoC show that the proposed initial device-setting and thermal-tuning mechanism confines the worst-case thermal-induced optical energy consumption to be on the order of tens of pJ/bit, by avoiding significant thermal-induced optical power loss caused by temperature-dependent wavelength shifts. Besides, it shows that the learning-based thermal-sensitive adaptive routing algorithm is able to find an optimal path with the minimum estimated thermal-induced optical power consumption for each communication pair. The proposed routing has a greater space for optimization, especially for applications with more long-distance traffic.

Wide-range average temperature measurements of convective fluid flows by using a schlieren system.

In the schlieren method, the deflection of light by the presence of an inhomogeneous medium is proportional to the gradient of its refractive index. In the presence of temperature variations in a fluid flow, the refraction index is related to the gas density by the Gladstone-Dale constant, which depends on the nature of the gas and the wavelength of light propagating in the medium. The deflection of light in a schlieren system is represented by intensity variations on the observation plane. Then, for a digital camera, the intensity level registered in each pixel depends mainly on the refractive index variation of the medium and exposure time. Therefore, if we regulate the intensity value of each pixel by controlling the exposure time, it is possible to adjust the temperature value measurements. In this way, a specific exposure time of a digital camera allows us to measure a determined range of temperature values. For that reason, in this study we determine the range of temperatures that can be measured with a digital camera for different exposure times. By doing this, a wide range of average temperature value fields can be obtained by summing up the temperature contribution of each exposure time. The basic idea in our approach to measure temperature by using a schlieren system is to relate the intensity level of each pixel in a schlieren image to the corresponding knife-edge position measured at the exit focal plane of the system. Our approach is applied to the measurement of temperature fields of the air convection caused by a heated rectangular metal plate (7.3 cm×12 cm) and a candle flame. We found that the maximum temperature values obtained for exposure times of 31.3, 15.7, 7.9, 3.9, and 2ms were 67.3°C, 122.6°C, 217.4°C, 364.3°C, and 524.0°C, respectively.

Wave mode diffusion and propagation in structural wave guide under Varying Temperature

A numerical approach is presented to study the guided wave propagation through periodic specimen with thermal dependence of material properties. There is a great interest in extending the skills of the wave finite element (WFE) method to figure out the variations in the wave propagation properties due to temperature fluctuations. Thermal effects on the dispersion curves thereby on group velocity are discussed. Comparisons between numerical results and analytical developments for various temperatures are given to prove the effectiveness of the proposed approach to predict the sensitivity of guided wave propagation characteristics in presence of temperature variations.

An Active Compensation System for the Temperature Dependence of SiPM Gain

Silicon photo-multiplier (SiPM) gain drifts due to temperature variations and this issue can be a source of relevant errors, for instance when the application requires high accuracy in the evaluation of the photopeak position, especially at low signal levels. In this paper we describe a compensation system that exploits a SiPM as temperature sensor and is able to keep the detector gain constant by means of fine adjustment of its bias voltage. The system is based on a feedback loop which measures the average amplitude of the dark pulses generated by the detector and compares it with a fixed reference, thus automatically correcting the device bias voltage and achieving constant amplitude of the dark pulses in presence of temperature variations. The same bias correction can be also applied to compensate the gain fluctuations of a SiPM not involved in the feedback loop, characterized by the same temperature dependence. The experimental results prove the effectiveness of the compensation system: for the SiPM used in the measurements, considering a temperature span of 10 $^\circ$ C, the system is able to reduce the corresponding variation of the dark pulse amplitude from about 22% to only 0.78%.

Approximating Optimal Estimation of Time Offset Synchronization With Temperature Variations

The paper addresses the problem of time offset synchronization in the presence of temperature variations, which lead to a non-Gaussian environment. In this context, regular Kalman filtering reveals to be suboptimal. A functional optimization approach is developed in order to approximate optimal estimation of the clock offset between master and slave. A numerical approximation is provided to this aim, based on regular neural network training. Other heuristics are provided as well, based on spline regression. An extensive performance evaluation highlights the benefits of the proposed techniques, which can be easily generalized to several clock synchronization protocols and operating environments.

Studying Interfacial Transport With Evanescent Wave-Based Particle Velocimetry and Thermometry

Interfacial phenomena due to surface forces are important in microfluidic devices with their relatively large surface areas and small volumes. This article reviews our recent studies measuring fluid velocities in Poiseuille and electrokinetically driven flows over the first ∼0.4 μm next to the wall from the motion of an ensemble of O(105) fluorescent particles illuminated by evanescent waves. Because the evanescent-wave intensity decays exponentially with wall-normal distance, the particle–wall separation can be determined from the brightness of each particle image, and used to estimate the steady-state distribution of the tracers near the wall. More recently, evanescent-wave illumination has been combined with fluorescence thermometry, to estimate water temperature fields from changes in the fluorescence intensity of aqueous fluorophore solutions. Poiseuille flow of a fluorescein solution at Reynolds numbers of 3.3 and 8.3 through a heated minichannel was illuminated with evanescent waves to measure solution temperatures at an average distance of 74 nm from the wall. The temperature results obtained over three different regions were in good agreement with numerical predictions of the wall surface temperature, even in the presence of temperature variations exceeding 9°C over the 1-mm width of the channel.

Non-linear dynamic instability of functionally graded plates in thermal environments

Geometrically non-linear parametric instability of functionally graded rectangular plates in thermal environments is investigated via a multi-degree-of-freedom energy approach. Non-linear higher-order shear deformation theory is used and the non-linear response to in-plane static and harmonic excitation in the frequency neighborhood of twice the fundamental mode is investigated. The boundary conditions are assumed to be simply supported movable. Numerical analyses are conducted by means of pseudo arc-length continuation and collocation technique to obtain force–amplitude relations in the presence of temperature variation in the thickness direction. The effect of volume fraction exponent and temperature variation on the onset of instability for both static and periodic in-plane excitation are fully discussed and the post-critical non-linear responses are obtained. Moreover, direct time integration of equations of motion is carried out and bifurcation diagrams, phase-space plots, Poincaré maps and time histories are obtained showing complex non-linear dynamics through period-doubling and Neimark–Sacker bifurcations.

Rayleigh-Bénard convection instability in the presence of temperature variation at the lower wall

This paper analyzes the two-dimensional viscous fluid flow between two parallel plates, where the lower plate is heated and the upper one is cooled. The temperature difference between the plates is gradually increased during a certain time period, and afterwards it is temporarily constant. The temperature distribution on the lower plate is not constant in x-direction, and there is longitudinal sinusoidal temperature variation imposed on the mean temperature. We investigate the wave number and amplitude influence of this variation on the stability of Rayleigh-Benard convective cells, by direct numerical simulation of 2-D Navier-Stokes and energy equation.