Heat Tracing Research Articles

LOW TEMPERATURE CRYSTALLIZATION BEHAVIOR OF NR BY DYNAMIC MECHANICAL ANALYSIS

ABSTRACT A fundamental study of low temperature crystallization of NR gum polymer (raw elastomer) was conducted using dynamic mechanical analysis (DMA) in oscillatory shear rheology mode. Isothermal crystallization was followed using DMA for crystallization temperatures ranging from −15 to −35 °C, with the maximum rate of crystallization noted at −25 °C. After the isothermal crystallization (annealing) for times from 6 to 9 h, DMA heating scans revealed two melting transitions (α and β) with locations that depended on the prior annealing temperature. The locations of these melting transitions were comparable with literature results for melting peaks by differential scanning calorimetry. At temperatures above these melting transitions, we identified two additional relaxations in the DMA heating trace that did not depend on the prior crystallization history. We also found evidence of the melt memory effect in polymer crystallization, which is discussed. During annealing at −25 °C, high cis-1,4 IR showed considerably slower and lower extent of crystallization than NR and crosslinked NR did not show noticeable crystallization within the 12-h experiment.

The Effect of Heat Tracing Installation for Wax Prevention on Onshore Buried Swampy Pipelines

Transporting crude oil using pipelines is a widely adopted method globally. In one segment owned by PT. XYZ, especially in swampy areas, the fluid temperature tends to drop below the wax appearance temperature (WAT) during oil transportation. This is due to the relatively low temperature in swamp areas caused by heat loss to the environment. The solubility of paraffin in crude oil drastically decreases as fluid temperature drops, causing wax molecules to precipitate and deposit on the cold pipe walls. PT. XYZ employs chemical treatment by adding a pour point depressant (PPD) to lower the pour point temperature (PPT). However, PPD is effective only at certain temperatures, necessitating a study for alternative treatments. Another method involves installing heaters on the pipeline to reduce the viscosity of transported crude oil and enhance its flowability, either through direct heating or heat tracing using insulation with low thermal conductivity. Therefore, in PT. XYZ's case, an analysis is required to identify locations where fluid temperature decreases occur to ensure precise heater installation. Various software tools, including OLGA, have been developed to predict and describe wax deposition phenomena and temperature decreases along the pipeline. OLGA software can simulate locations of fluid temperature decreases in the pipeline, estimate heat loss along the pipeline, and simulate heat tracing technologies to prevent wax deposition. Simulation results indicate that wax deposition can be prevented by installing skin effect heat tracing with a heating power of 15 W/m and insulated with 2-inch aerogel, maintaining the oil temperature downstream at 157.34°F, well above the desired 115°F threshold.

Multi-task learning for hand heat trace time estimation and identity recognition

The thermal imager can capture the invisible thermal trace, and the potential information contained in the thermal trace can be extracted through the identification and analysis of the infrared thermal trace, such as the identity information and time information of the trace. This technology has great application value in criminal investigation, military and other fields. However, with the passage of time, the heat traces will gradually fade, and the intra-class distances will gradually increase. For hand heat trace, the trace may exhibit significant variations at different time points or in different states. This will pose challenges for extracting potential information and present significant challenges for model recognition. Therefore, we propose a multi task framework using deep convolutional neural networks (MTLHand) to jointly handle the two tasks of heat trace identification and heat trace departure time estimation. It can learn invariant representations of thermal trace identities, better capturing the dynamic changes in palmprint data, to enhance the accuracy of identity recognition. Specifically, soft threshold is inserted as nonlinear transformation layers into an improved ResNet to extract deep mixed hand trace features. The mixed features are decomposed into identity related features and time related features through spatial attention and channel attention. Use the multi task training method to carry out the corresponding learning tasks. In addition, we collected and constructed an infrared hand heat trace dataset containing labels such as departure time, gender, hand posture, identity category, etc., to promote the development of heat trace research. Experiments on this dataset show that our method is superior to other deep learning methods for the specific task of infrared heat trace recognition, and the identification accuracy can reach 83.48 %. In the trace leaving time estimation task, the recognition error rate is 18 % if the residual value between the estimated time and the real time is less than 60 s, and 3.55 % if the residual value is less than 120 s.

Indications of preferential groundwater seepage feeding northern peatland pools

Groundwater seepage from underlying permeable glacial sedimentary structures, such as eskers, has been hypothesized to directly feed pools in northern peat bogs. These hypotheses directly contradict classical peat bog models for ombrogenous systems, wherein meteoric water is the sole water input to these systems. Variations in the underlying mineral sediment in contact with the peat imply that unrecognized hydrogeologic connectivity may exist with pools in northern peat bogs, particularly where high permeability materials are in contact with the peat. Seepage dynamics originating from these structural variations were investigated using a suite of thermal and hydrogeophysical methods deployed around pools in a peat bog of northeastern Maine, USA. Thermal characterization methods mapped anomalies that were confirmed as matrix seepage or preferential flow pathways (PFPs). Geochemical methods were employed at identified thermal anomalies to confirm upwelling of solute-rich groundwater. Conduits around pools were associated with surficial terminations of suspected peat pipes, based on the inference of pathways extending down into the peat, that focus flow through PFPs in the peat matrix. Discharge also occurred through the peat matrix adjacent to suspected pipe structures and matrix seepage rates were quantified using analysis of diurnal temperature signals recorded at multiple depths. Seepage rates, with a maximum of nearly 0.4 m/d, were measured at localized points around pools. Periods of synchronized temperatures paired with highly muted diurnal temperature signals, recorded in diurnal temperature with depth data, were interpreted qualitatively as activation of strong upward discharge rates through suspected peat pipes. These time periods correlated strongly with local precipitation events around the peatland. Ground-penetrating radar surveys revealed discontinuities in the low permeability glacio-marine clay at the mineral sediment-peat interface, interpreted to be regional glacial esker deposits, which were located beneath and around pools. Heat tracing, specific conductance contrasts, seepage rates, and trace metal concentrations all imply groundwater seepage originating from underlying permeable glacial esker deposits and directly sourcing pools. Preferential groundwater inputs into northern peat bogs may play a key role in developing and maintaining pool systems, with enhanced solute transport impacting peatland ecology, water resources, and carbon cycling.

Reducing the level of infrared radiation of a ground vehicle during its movement

Problem. Reducing the visibility of a ground vehicle makes it possible to increase its survivability and provide conditions for the performance of assigned tasks. The development of approaches to the analysis of the conditions for the formation of a heat trace from the engine of the ground vehicle is an extremely important scientific and practical task. Goal. The purpose of the work was to carry out comparative numerical modelling to assess the effectiveness of diluting the EG flow of the engine of the ground vehicle with atmospheric air to reduce their temperature. Methodology. Using the method of finite volumes, a comparative numerical experiment was conducted in a three-dimensional stationary setup. The possibility of sucking atmospheric air with the standard nozzle of the ejector was quantified. Results. The study shows that the addition of atmospheric air can effectively reduce the temperature of exhaust gases. The use of a regular ejection system allows to reduce the temperature of exhaust gases by 10-12 degrees without additional energy consumption. Originality. Using the method of a comparative numerical experiment, the effectiveness of adding atmospheric air to the exhaust gases of a diesel engine in order to suppress the heat trace was evaluated. Practical value. An approach to reducing the temperature of the exhaust gases of the ground vehicle engine is proposed, that allows to decrease its visibility in the infrared radiation spectrum without additional energy consumption.

Full-scale tests of deicing with seawater

Sea-spray icing is one of the major hazards for small- and medium-sized vessels in polar regions. Predominant anti- and deicing measures include prevention by heeding the weather forecasts and avoiding high-risk situations, protection by enclosing exposed and high-priority areas, manual ice removal by personnel, heat tracing and surplus heat. Energy is in limited supply on vessels, and alternative ways of ice protection are sought after. Seawater is readily available, and as evident from wave-washing, either naturally occurring or increased by provocative maneuvering, seawater can hold an efficient deicing capacity. This study contains knowledge gained from four separate full-scale deicing tests. Deicing is achieved during the field tests by utilizing the vessel's external fire sprinkler systems and in one case a fire hose. To the author's knowledge, no recent tests with deicing of vessels using flushing seawater have been performed, and this article is considered a first step towards evaluating the viability of the method. Targeted high-volume, low-pressure systems seem to be an effective method for deicing, particularly combined with favorable design. However, because of the risk of increased icing or freezing run-off the method is suitable for vessels and structures with sufficient run-off capabilities. Vessel safety can be improved by incorporating the proposed method.

Deep soft threshold feature separation network for infrared handprint identity recognition and time estimation

With the development of hardware devices, infrared technology has become an important detection method in criminal investigation, military and other fields. Infrared technology can capture the thermal infrared information of targets, achieve efficient and rapid individual identification, provide important technological support for crime investigation, improve case solving rate and public safety level. However, infrared technology still faces some difficulties. Due to factors such as environmental temperature changes and heat transfer, the infrared images captured over time gradually blur, resulting in highly aliased image features and difficulty in extracting effective information. This article addresses this issue by combining the specific tasks of infrared fingerprint identity recognition and time estimation. By analyzing the captured thermal traces to predict the target identity and departure time, a deep soft threshold feature separation (DSTFS) network is proposed. This network effectively improves the accuracy of identity recognition and time estimation by separating the characteristics of identity information and time information. Specifically, this article is based on the ResNet backbone network, extracting common features through shallow residual convolution blocks, extracting corresponding features for different tasks using branch residual convolution blocks, and introducing spatial and channel attention mechanisms to solve the problems of deep blur and feature separation. In order to enhance the model's expressive power, the soft threshold activation function SPRelu was adopted. By dynamically balancing the separation of features to learn weights, the weight balancing problem is solved, and periodic validation is used to evaluate task performance. According to the task requirements, we collected infrared fingerprint images of multiple testers and constructed an infrared hand heat trace dataset with labels such as departure time, gender, hand posture, and identity category as experimental data. Through the analysis of experimental results, our proposed deep feature separation network has better identity prediction results compared to other deep learning models in infrared fingerprint identity recognition and time estimation tasks. At the same time, it performs well in time estimation tasks, with lower error rates and higher stability.

Detecting reorganization in semicrystalline polymers during heating: Insights from Fast Scanning Chip Calorimetry coupled with real-time optical microscopy

Thermal behavior of semicrystalline polymers is notoriously complex due to the metastable nature of polymer crystals. This complexity is evidenced in the multiple melting endotherms frequently observed in the heating traces of various plastics, a phenomenon known as ‘multiple melting behavior’. Extensive research indicates that calorimetric analysis alone may not suffice to fully elucidate the processes occurring during thermal experiments. In this study, we introduce an experimental setup that integrates Fast Scanning Chip Calorimetry, or nanocalorimetry, with real-time polarized optical microscopy. This combination enables in-situ morphological observations during rapid heating/cooling experiments. The setup not only complements thermal analysis but also rivals the capabilities of fast in situ X-ray scattering experiments conducted at synchrotron sources. Our findings show that the obtained data help in identifying melting/recrystallization processes and, therefore, enable the determination of the critical heating rate above which reorganization processes during heating are kinetically bypassed. This ensures that the thermal events detected in calorimetric curves are exclusively due to the initial sample structure, without being influenced by any reorganization that may occur during the heating process.

Demonstration of 3.5 MWth Parabolic Trough With Ternary Molten Salt at the Évora Molten Salt Platform

Commercial solar thermal parabolic trough power plants use thermal oil as a heat transfer medium in the solar field. Within the framework of the “High Performance Solar 2” (HPS2) research project a molten salt parabolic trough demonstration plant was commissioned in summer 2021 in Évora, Portugal. Since then it has been operated for more than 5.500 h between 180°C and 500 °C, jointly by the University of Évora, DLR and TSK Flagsol. This article presents the main steps of cold and hot commissioning as well as experiences gained in plant operation. It has been shown that filling a preheated solar field with ternary molten salt is not critical, but its drainage can be challenging depending on the quality of the heat tracing and the solar field slope.

Analysis of sensitivity to hydrate blockage risk in natural gas gathering pipeline

During the operational process of natural gas gathering and transmission pipelines, the formation of hydrates is highly probable, leading to uncontrolled movement and aggregation of hydrates. The continuous migration and accumulation of hydrates further contribute to the obstruction of natural gas pipelines, resulting in production reduction, shutdowns, and pressure build-ups. Consequently, a cascade of risks is prone to occur. To address this issue, this study focuses on the operational process of natural gas gathering and transmission pipelines, where a comprehensive framework is established. This framework includes theoretical models for pipeline temperature distribution, pipeline pressure distribution, multiphase flow within the pipeline, hydrate blockage, and numerical solution methods. By analyzing the influence of inlet temperature, inlet pressure, and terminal pressure on hydrate formation within the pipeline, the sensitivity patterns of hydrate blockage risks are derived. The research indicates that reducing inlet pressure and terminal pressure could lead to a decreased maximum hydrate formation rate, potentially mitigating pipeline blockage during natural gas transportation. Furthermore, an increase in inlet temperature and terminal pressure, and a decrease in inlet pressure, results in a displacement of the most probable location for hydrate blockage towards the terminal station. However, it is crucial to note that operating under low-pressure conditions significantly elevates energy consumption within the gathering system, contradicting the operational goal of energy efficiency and reduction of energy consumption. Consequently, for high-pressure gathering pipelines, measures such as raising the inlet temperature or employing inhibitors, electrical heat tracing, and thermal insulation should be adopted to prevent hydrate formation during natural gas transportation. Moreover, considering abnormal conditions such as gas well production and pipeline network shutdowns, which could potentially trigger hydrate formation, the installation of methanol injection connectors remains necessary to ensure production safety.

Spectral asymptotics of elliptic operators on manifolds

The study of spectral properties of natural geometric elliptic partial differential operators acting on smooth sections of vector bundles over Riemannian manifolds is a central theme in global analysis, differential geometry and mathematical physics. Instead of studying the spectrum of a differential operator [Formula: see text] directly one usually studies its spectral functions, that is, spectral traces of some functions of the operator, such as the spectral zeta function [Formula: see text] and the heat trace [Formula: see text]. The kernel [Formula: see text] of the heat semigroup [Formula: see text], called the heat kernel, plays a major role in quantum field theory and quantum gravity, index theorems, non-commutative geometry, integrable systems and financial mathematics. We review some recent progress in the study of spectral asymptotics. We study more general spectral functions, such as [Formula: see text], that we call quantum heat traces. Also, we define new invariants of differential operators that depend not only on the eigenvalues but also on the eigenfunctions, and, therefore, contain much more information about the geometry of the manifold. Furthermore, we study some new invariants, such as [Formula: see text], that contain relative spectral information of two differential operators. Finally, we show how the convolution of the semigroups of two different operators can be computed by using purely algebraic methods.

Weyl's law for singular Riemannian manifolds

We study the asymptotic growth of the eigenvalues of the Laplace-Beltrami operator on singular Riemannian manifolds, where all geometrical invariants appearing in classical spectral asymptotics are unbounded, and the total volume can be infinite. Under suitable assumptions on the curvature blow-up, we show how the singularity influences the Weyl's asymptotics. Our main motivation comes from the construction of singular Riemannian metrics with prescribed non-classical Weyl's law. Namely, for any non-decreasing slowly varying function υ we construct a singular Riemannian structure whose spectrum is discrete and satisfiesN(λ)∼ωn(2π)nλn/2υ(λ). Examples of slowly varying functions are log⁡λ, its iterations logk⁡λ=logk−1⁡log⁡λ, any rational function with positive coefficients of logk⁡λ, and functions with non-logarithmic growth such as exp⁡((log⁡λ)α1…(logk⁡λ)αk) for αi∈(0,1). A key tool in our arguments is a new quantitative estimate for the remainder of the heat trace and the Weyl's function on Riemannian manifolds, which is of independent interest.

Hydrogeochemical characterization and precursor anomalies of hot springs in the North Tianshan orogen

The North Tianshan orogen consists of a series of thrust faults and is the most seismic region in China. In this paper, the characteristics of hot springs in the North Tianshan orogen are analyzed. Hydrochemical analysis of 13 hot springs and four mud volcanoes reveals that the cations of most hot springs are mainly Na+, while the anions are mainly Cl−.Atmospheric precipitation is the main recharge source for the hot springs in the study area, with recharge heights ranging from −9 to 2344 m. Heat storage analysis and trace element results showed deep fluid characteristics, which is consistent with deep circulation processes and regional extrusion pressure background. In addition, continuous measurements of six hot springs were conducted once every three days. The results showed that Cl− and SO42− concentration anomalies occurred before several earthquakes of ML4.0 in the North Tianshan orogen. The hot springs SWQ, HTB, and WS, which have deeper circulation depths, show better responsiveness than X10, which has a shallow circulation depth. The deep circulation of hot springs increases fault sliding friction, which contributes to energy accumulation and strong seismogenesis, and participates in the seismogenesis process. Therefore, continuous monitoring of ion concentrations of deep-circulation hot springs can help identify effective precursor anomalies in the North Tianshan orogen.

Thermal Performance Analysis of a Mounded Liquid Ethylene Storage Tank

AbstractA model including the tank body and the external environment is developed to investigate the temperature field of a mounded liquid ethylene storage tank system during long‐term placement. Since the external environment always changes, it is introduced by writing user‐defined functions (UDFs). The effects of external environment and structural parameters on the temperature field are analyzed to provide reference for the design of the heat tracing devices of the storage tank system. The results indicate that the increase of tank quantities substantially reduces the outer‐surface temperature of the cold insulation structure. The increase in tank spacing and thickness of the cold insulation structure weakens the interaction of adjacent tanks and raises the outer‐surface temperature of the cold insulation structure.

Challenges & Improvised Methods for a Successful Electrical Heat Tracing Design & Engineering on A Mega-Size Project

Challenges & Improvised Methods for a Successful Electrical Heat Tracing Design & Engineering on A Mega-Size Project

Acquisition of Spatial and Temporal Characteristics of Shallow Groundwater Movement Based on Long-Term Temperature Time Series in the Kangding Area, Eastern Tibetan Plateau

Heat has been widely used as a groundwater tracer to determine groundwater flow direction and velocity in a way that is ubiquitous, low-cost, environmentally friendly, and easy to use. However, temperature observations are generally short-term and small-scale, meaning they may not be able to reflect long-term changes in the characteristics of groundwater movement. In this study, we utilize 515 days of temperature data, collected from four measurement points in the Kangding area of the eastern Tibetan Plateau, in order to determine the spatial and temporal distribution of groundwater flow velocities using different analytical heat tracing methods. An analysis is conducted to evaluate the impact of thermal parameter uncertainties on the calculation of flow velocity, and a comparison is undertaken between the results of the phase, amplitude, and combined amplitude-phase methods. We subsequently discuss the relationship between flow velocity changes and precipitation. The results show that the estimated flow velocity is more susceptible to the volumetric heat capacity of the saturated sediment than it is to thermal conductivity. The phase method is more suitable for use in calculations in the study area, indicating that precipitation significantly impacts the flow velocity and that this impact is more pronounced in areas with flat terrain compared to areas with significant variation in elevation. Our research provides a comparative study of the heat tracing methods in areas with varied terrains and offers new evidence for the impact of precipitation and topography on groundwater infiltration.

Multimaterial Printing of Liquid Crystal Elastomers with Integrated Stretchable Electronics.

Liquid crystal elastomers (LCEs) have grown in popularity in recent years as a stimuli-responsive material for soft actuators and shape reconfigurable structures. To make these material systems electrically responsive, they must be integrated with soft conductive materials that match the compliance and deformability of the LCE. This study introduces a design and manufacturing methodology for combining direct ink write (DIW) 3D printing of soft, stretchable conductive inks with DIW-based "4D printing" of LCE to create fully integrated, electrically responsive, shape programmable matter. The conductive ink is composed of a soft thermoplastic elastomer, a liquid metal alloy (eutectic gallium indium, EGaIn), and silver flakes, exhibiting both high stretchability and conductivity (order of 105 S m-1). Empirical tuning of the LCE printing parameters gives rise to a smooth surface (<10 μm) for patterning the conductive ink with controlled trace dimensions. This multimaterial printing method is used to create shape reconfigurable LCE devices with on-demand circuit patterning that could otherwise not be easily fabricated through traditional means, such as an LCE bending actuator able to blink a Morse code signal and an LCE crawler with an on/off photoresistor controller. In contrast to existing fabrication methodologies, the inclusion of the conductive ink allows for stable power delivery to surface mount devices and Joule heating traces in a highly dynamic LCE system. This digital fabrication approach can be leveraged to push LCE actuators closer to becoming functional devices, such as shape programmable antennas and actuators with integrated sensing.

Spectral invariants of the magnetic Dirichlet-to-Neumann map on Riemannian manifolds

This paper is devoted to investigating the heat trace asymptotic expansion associated with the magnetic Steklov problem on a smooth compact Riemannian manifold (Ω, g) with smooth boundary ∂Ω. By computing the full symbol of the magnetic Dirichlet-to-Neumann map M, we establish an effective procedure, by which we can calculate all the coefficients a0, a1, …, an−1 of the asymptotic expansion. In particular, we explicitly give the first four coefficients a0, a1, a2, and a3. They are spectral invariants, which provide precise information concerning the volume and curvatures of the boundary ∂Ω and some physical quantities.

Paired Air and Stream Temperature Analysis (PASTA) to Evaluate Groundwater Influence on Streams

AbstractGroundwater is critical for maintaining stream baseflow and thermal stability; however, the influence of groundwater on streamflow has been difficult to evaluate at broad spatial scales. Techniques such as baseflow separation necessitate streamflow records and do not directly indicate whether groundwater inflow may be sourced from more dynamic shallow flowpaths. We present a web tool application PASTA (Paired Air and Stream Temperature Analysis; https://cuahsi.shinyapps.io/pasta/) that capitalizes on increased public stream temperature data availability and large‐scale, gridded climate observations to provide new and efficient insights regarding relative groundwater influence on streams. PASTA analyzes paired air and stream water temperature signals to evaluate spatiotemporal patterns in stream thermal sensitivity and relative groundwater influence, including inference regarding the dominant source groundwater depth (shallow or deep (i.e., approximately &gt;6 m depth)). The tool is linked to publicly available stream temperature datasets and accepts user‐uploaded datasets. As local air temperature is not often monitored, PASTA pulls daily air temperature data from the comprehensive Daymet products when directly measured data are unavailable, allowing the repurposing of existing stream temperature data. After data are selected or uploaded, the tool (a) fits sinusoidal curves of daily stream and air temperatures by year (water or calendar) to indicate groundwater influence characteristics and (b) performs linear regressions for stream versus air temperatures to indicate stream thermal sensitivity. Results are exported in ASCII file format, creating an efficient and approachable analysis tool for the adoption of newly developed heat tracing analysis from stream reach to landscape scales.

Interactive robot teaching based on finger trajectory using multimodal RGB-D-T-data.

The concept of Industry 4.0 brings the change of industry manufacturing patterns that become more efficient and more flexible. In response to this tendency, an efficient robot teaching approach without complex programming has become a popular research direction. Therefore, we propose an interactive finger-touch based robot teaching schema using a multimodal 3D image (color (RGB), thermal (T) and point cloud (3D)) processing. Here, the resulting heat trace touching the object surface will be analyzed on multimodal data, in order to precisely identify the true hand/object contact points. These identified contact points are used to calculate the robot path directly. To optimize the identification of the contact points we propose a calculation scheme using a number of anchor points which are first predicted by hand/object point cloud segmentation. Subsequently a probability density function is defined to calculate the prior probability distribution of true finger trace. The temperature in the neighborhood of each anchor point is then dynamically analyzed to calculate the likelihood. Experiments show that the trajectories estimated by our multimodal method have significantly better accuracy and smoothness than only by analyzing point cloud and static temperature distribution.