Thermal Metrics Research Articles

Development of a hybrid behavioural and thermal adaptive building envelope

This study focuses on the design of behavioural mechanisms for a hybrid informed adaptive envelope. Based on a full-scale experimental demonstrator, including a material responsive and a sensor–processing–actuation adaptive system, quantitative and qualitative methods are applied to identify, describe and study behavioural modes of the adaptive envelope. Through sensor data values and observations, the study finds that the adaptive response patterns are best based on subjective, human-mapped sensations, rather than prescribed environmental comfort, numeric-based sensor values. Those adaptive response patterns should account for change in tempi of the environment, occupier and envelope to establish advanced cause and effect relations, beyond generic thermal comfort performance metrics.

Development of a new metric to characterise the buildings thermal performance in a temperate climate

The paper describes the development of a new metric to evaluate the thermal performance of residential houses for temperate climates, named the Adaptive Thermal Metric (ATM). The proposed ATM helps the evaluation of the thermal performance of an entire house by finding the internal air temperature of the building using Computational Fluid Dynamics (CFD) simulation then computes the fraction of time over which the internal air temperature of the house stayed within the 90% or 80% adaptive thermal comfort limits (designated ATM90 and ATM80 respectively).The adaptive thermal comfort approach allows inhabitants to choose an adequate range of internal air temperatures by implementing other adaptive practices such as changing clothes, opening windows, or using low energy solutions (e.g. fans) to adjust their thermal comfort level. The new metric uses temperature to assess a building's thermal performance. This differs from other commonly conventional approaches, which are established based on the amount of energy usage required to sustain an inhabitant's thermal comfort.To verify the modelling technique, the CFD simulated internal air temperatures were compared with the actual temperatures recorded for four full-scale housing test modules, each incorporating a different walling system. This comparison yielded an average accuracy of 93% at any given time for all simulated modules over the 12-month simulation period.Using the above CFD approach, the ATMs were calculated for each building test module over the studied period. The final results showed that the best thermal performance module was the Insulated Cavity Brick module (InsCB), followed by the Insulated Reverse Brick Veneer (InsRBV), Insulated Brick Veneer (InsBV) and Cavity Brick (CB) modules. These findings were accordant with both the house evaluation software used in Australia (i.e. AccuRate) and the earlier results on the walling systems research done by the University of Newcastle in Australia, which were used to assess the accuracy of the ATM. The results indicated that the ATM has the potential to be used as an alternative building evaluation technique to assess the overall building thermal performance in temperate climates.

TRAC: A Thermal Resistance Advanced Calculator for Electronic Packages

This paper presents a novel simulation tool named thermal resistance advanced calculator (TRAC). Such a tool allows the straightforward definition of a parametric detailed thermal model of electronic packages with Manhattan geometry, in which the key geometrical details and thermal properties can vary in a chosen set. Additionally, it can apply a novel model-order reduction-based approach for the automatic and fast extraction of a parametric compact thermal model of such packages. Furthermore, it is suited to automatically determine the joint electron device engineering council (JEDEC) thermal metrics for any choice of parameters in a negligible amount of time. The tool was validated through the analysis of two families of quad flat packages.

The Influences of Various Testing Conditions on the Evaluation of Household Biomass Pellet Fuel Combustion

Direct combustion of solid biomass fuel is one of the most common energy sources in developing countries. Evaluation of technology for household biomass pellet fuel combustion is critical, since promoting poorly designed devices may have risks due to exposure to high levels of emissions. This study evaluated the effects of various testing conditions on a top-lit forced-up-draft semi-gasifier cooking stove. An orthogonal test was designed with different fuel masses, chamber heights, air supply rates, and ending points. The investigation showed that using forced secondary air and more fuel tended to improve both thermal and gas emissions performance. The ending points did not have significant effects on thermal efficiency or the carbon dioxide emission factor, but did affect particulate matter emission. A relatively lower chamber height demonstrated better performance on thermal metrics. However, a taller flame had better performance on particulate matter emission factors. The results of the indicators reported by different bases, such as fuel mass-based or useful energy-based were also quite different. The study showed that different testing conditions had significant effects on combustion performances. Testing sequences and emission factors should be reviewed and defined clearly when forming testing methods and standards for biomass pellet fuel combustion.

Thermal regime metrics and quantifying their uncertainty for North American streams

AbstractUnderstanding and characterizing thermal regimes is gaining popularity, but there has been little assessment of the sources and magnitudes of uncertainty among different thermal metrics. Understanding how the quantity of data influence estimates of metrics and the characterization of thermal regime is critical to resource management. We examine the influence of record length on the uncertainty of estimation for commonly used thermal metrics including mean annual maximum and minimum, timing of the annual maximum and minimum, mean annual temperature range, mean weekly maximum temperature, July maximum, minimum, and range. We selected 19 sites from U.S. Geological Survey hydrometric station network to represent stations with both small and large drainage areas across the ecoregions of the contiguous United States with at least 20 years of daily stream temperature data. We also selected 54 sites from Water Survey of Canada's hydrometric network with at least 7 years of sub‐daily data for the province of Ontario. Randomizing a progressively increasing set of years used to calculate estimates of each metric provided the percentile confidence bands that were compared with various thresholds of acceptable certainty. Bootstrap confidence bands quickly decreased in width with increasing record length and approached an acceptable level at an average of 12 years for daily data metrics. Metrics calculated using the sub‐daily data required approximately 3 years of data. The timing of annual minimum and maximum temperatures required the greatest amount of data to reduce bias to an acceptable level.

Full-field thermal imaging of quasiballistic crosstalk reduction in nanoscale devices

Understanding nanoscale thermal transport is of substantial importance for designing contemporary semiconductor technologies. Heat removal from small sources is well established to be severely impeded compared to diffusive predictions due to the ballistic nature of the dominant heat carriers. Experimental observations are commonly interpreted through a reduction of effective thermal conductivity, even though most measurements only probe a single aggregate thermal metric. Here, we employ thermoreflectance thermal imaging to directly visualise the 2D temperature field produced by localised heat sources on InGaAs with characteristic widths down to 100 nm. Besides displaying effective thermal performance reductions up to 50% at the active junctions in agreement with prior studies, our steady-state thermal images reveal that, remarkably, 1–3 μm adjacent to submicron devices the crosstalk is actually reduced by up to fourfold. Submicrosecond transient imaging additionally shows responses to be faster than conventionally predicted. A possible explanation based on hydrodynamic heat transport, and some open questions, are discussed.

State of the art of thermal characterization of electronic components using computational fluid dynamic tools

PurposeLatest Computational Fluid Dynamics (CFDs) tools allow modeling more finely the conjugate thermo-fluidic behavior of a single electronic component mounted on a Printed Wiring Board (PWB). A realistic three-dimensional representation of a large set of electric copper traces of its composite structure is henceforth achievable. The purpose of this study is to confront the predictions of the fully detailed numerical model of an electronic board to a set of experiment results to assess their relevance.Design/methodology/approachThe present study focuses on the case of a Ball Grid Array (BGA) package of 208 solder balls that connect the component electronic chip to the Printed Wiring Board. Its complete geometrical definition has to be coupled with a realistic board layers layout and a fine description of their numerous copper traces to appropriately predict the way the heat is spread throughout that multi-layer composite structure. The numerical model computations were conducted on four CFD software then compare to experiment results. The component thermal metrics for single-chip packages are based on the standard promoted by the Joint Electron Device Engineering Council (JEDEC), named JESD-51. The agreement of the numerical predictions and measurements has been done for free and forced convection.FindingsThe present work shows that the numerical model error is lower than 2 per cent for various convective boundary conditions. Moreover, the establishment of realistic numerical models of electronic components permits to properly apprehend multi-physics design issues, such as joule heating effect in copper traces. Moreover, the practical modeling assumptions, such as effective thermal conductivity calculation, used since decades, for characterizing the thermal performances of an electronic component were tested and appeared to be tricky. A new approach based on an effective thermal conductivity matrix is investigated to reduce computation time. The obtained numerical results highlight a good agreement with experimental data.Research limitations/implicationsThe study highlights that the board three-dimensional modeling is mandatory to properly match the set of experiment results. The conventional approach based on a single homogenous layer using effective thermal conductivity calculation has to be banned.Practical implicationsThe thermal design of complex electronic components is henceforth under increasing control. For instance, the impact of gold wire-bonds can now be investigated. The three-dimensional geometry of sophisticated packages, such as in BGA family, can be imported with all its internal details as well as those of its associated test board to build a realistic numerical model. The establishment of behavioral models such as DELPHI Compact Thermal Models can be performed on a consistent three-dimensional representation with the aim to minimize computation time.Originality/valueThe study highlights that multi-layer copper trace plane discretization could be used to strongly reduce computation time while conserving a high accuracy level.

Magneto‐Thermal Metrics Can Mirror the Long‐Term Intracellular Fate of Magneto‐Plasmonic Nanohybrids and Reveal the Remarkable Shielding Effect of Gold

Multifunctional nanoparticles such as magneto‐plasmonic nanohybrids are rising theranostic agents. However, little is yet known of their fate within the cellular environment. In order to reach an understanding of their biotransformations, reliable metrics for tracking and quantification of such materials properties during their intracellular journey are needed. In this study, their long‐term (one month) intracellular fate is followed within stem‐cell spheroids used as tissue replicas. A set of magnetic (magnetization) and thermal (magnetic hyperthermia, photothermia) metrics is implemented to provide reliable insightsinto the intracellular status. It shows that biodegradation is modulated by the morphology and thickness of the gold shell. First a massive dissolution of the iron oxide core (nanoflower‐like) is observed, starting with dissociation of the multigrain structure. Second, it is demonstrated that an uninterrupted gold shell can preserve the magnetic core and properties (particularly magnetic hyperthermia). In addition to the magnetic and thermal metrics, intracellular high‐resolution chemical nanocartography evidences the gradual degradation of the magnetic cores. It also shows different transformation scenarios, from the release of small gold seeds when the magnetic core is dissolved (interesting for long‐term elimination) to the protection of the magnetic core (interesting for long‐term therapeutic applicability).

StreamThermal: A Software Package for Calculating Thermal Metrics from Stream Temperature Data

Improving quality and better availability of continuous stream temperature data allow natural resource managers, particularly in fisheries, to understand associations between different characteristics of stream thermal regimes and stream fishes. However, there is no convenient tool to efficiently characterize multiple metrics reflecting stream thermal regimes with the increasing amount of data from continuously recording data loggers. This article describes a software program packaged as a library in R to facilitate this process. With this freely available package, users will be able to quickly summarize metrics that describe five categories of stream thermal regimes: magnitude, variability, frequency, timing, and rate of change. The installation and usage instruction of this package, the definition of calculated thermal metrics, as well as the output format from the package are described, along with an application showing the utility for multiple metrics. We believe that this package can be widely utilized by interested stakeholders and can greatly assist future fisheries studies.

Assessing the Skill and Value of Seasonal Thermal Stress Forecasts for Coral Bleaching Risk in the Western Pacific

AbstractOver the last 30 years, coral reefs around the world have been under considerable stress because of increasing anthropogenic pressures, overfishing, pollution, and climate change. A primary stress factor is anomalously warm water events, which can cause mass coral bleaching and widespread reef damage. Forecasts of sea surface temperature (SST) and the associated risk of coral bleaching can assist managers, researchers, and other stakeholders in monitoring and managing coral reef resources. At the Australian Bureau of Meteorology, monthly forecasts of SST and thermal stress metrics have been developed that are based on a dynamical seasonal prediction system known as the Predictive Ocean Atmosphere Model for Australia (POAMA). To support the effective use of these forecasts in risk-based decision-making frameworks in the western and central tropical Pacific Ocean, the skill of these forecast tools in this region was assessed using several categorical forecast skill scores. It was found that the model provides SST forecasts with statistically significant skill up to 8 months in advance (correlation coefficient > 0.4; p = 0.05) across the region. The highest skill (r > 0.9) was achieved over the central equatorial Pacific Ocean, likely as a result of this region’s strong relationship with the El Niño–Southern Oscillation (ENSO). Potential forecast value was assessed using a simplified cost–loss ratio decision model, which indicated that POAMA’s seasonal hot-spot thermal stress forecasts can provide valuable information to reef management and policy makers in the western Pacific region.

Modulated-Power Implantable Neuromodulation Devices and Their Impact on Surrounding Tissue Temperatures

This project was intended to determine whether the preprogrammed time-varying recharge protocol for a battery incased in a neuromodulation implant can give rise to tissue temperatures that surpass a safe level or are otherwise benign. The study included the development of a highly accurate model of all the thermal processes that are activated by the recharging of the battery contained within the neuromodulation implant. The model was implemented by numerical simulations performed for several realistic operating conditions. The computed spatial and temporal tissue temperature distributions were employed to estimate possible tissue damage by making use of two independent methodologies. Independent calorimeter-based experiments were performed to provide validation for the calculated rates of heat generation in the coils of the implant. Spatial and temporal tissue temperature distributions extracted from the numerical simulations revealed the thermal effects associated with several realistic operating protocols. None of the operating protocols gave rise to temperatures above 42℃. Numerical values of thermal tissue damage metrics were determined and compared with accepted values which correspond to the absence and the presence of tissue damage. The experimentally determined rate of heat generation in the implant coils validated that from electrical measurements to within 2%. Both the tissue temperature results and the thermal damage metrics found no evidence of tissue injury when time-varying preprogrammed protocols are used in the recharging of neuromodulation implant-encased batteries.

The ability of winter grazing to reduce wildfire size and fire-induced plant mortality was not demonstrated: a comment on Davies et al. (2015)

A recent study by Davies et al. sought to test whether winter grazing could reduce wildfire size, fire behaviour and intensity metrics, and fire-induced plant mortality in shrub–grasslands. The authors concluded that ungrazed rangelands may experience fire-induced mortality of native perennial bunchgrasses. The authors also presented several statements regarding the benefits of winter grazing on post-fire plant community responses. However, we contend that the study by Davies et al. has underlying methodological errors, lacks data necessary to support their conclusions, and does not provide a thorough discussion on the effect of grazing on rangeland ecosystems. Importantly, Davies et al. presented no data on the post-fire mortality of the perennial bunchgrasses or on the changes in plant community composition following their experimental fires. Rather, Davies et al. inferred these conclusions based on their observed fire behaviour metrics of maximum temperature and a term described as the ‘heat load’. However, we contend that neither metric is appropriate for describing the heat flux impacts on plants. This lack of post-fire data, several methodological errors and the use of inappropriate thermal metrics limit the authors’ ability to support their stated conclusions.

Distance makes the difference in thermography for ecological studies

Surface temperature drives many ecological processes and infrared thermography is widely used by ecologists to measure the thermal heterogeneity of different species' habitats. However, the potential bias in temperature readings caused by distance between the surface to be measured and the camera is still poorly acknowledged. We examined the effect of distance from 0.3 to 80m on a variety of thermal metrics (mean temperature, standard deviation, patch richness and aggregation) under various weather conditions and for different structural complexity of the studied surface types (various surfaces with vegetation). We found that distance is a key modifier of the temperature measured by a thermal infrared camera. A non-linear relationship between distance and mean temperature, standard deviation and patch richness led to a rapid under-estimation of the thermal metrics within the first 20m and then only a slight decrease between 20 and 80m from the object. Solar radiation also enhanced the bias with increasing distance. Therefore, surface temperatures were under-estimated as distance increased and thermal mosaics were homogenized at long distances with a much stronger bias in the warmer than the colder parts of the distributions. The under-estimation of thermal metrics due to distance was explained by atmospheric composition and the pixel size effect. The structural complexity of the surface had little effect on the surface temperature bias. Finally, we provide general guidelines for ecologists to minimize inaccuracies caused by distance from the studied surface in thermography.

Prediction of Daylighting and Energy Performance Using Artificial Neural Network and Support Vector Machine

The computerized building design has been developed to optimize building design. Machine learning techniques are explored to help predict building design performance. However, in the current building design tools, the optimization techniques have not been integrated closely with the computerized building design tool. Only a few tools add some optimization methods such as genetic algorithms. The aim of the paper is to use machine learning techniques to predict the daylighting metrics such as illuminance and thermal metrics for different combinations of window glazing transmittances, weather conditions and blind reflectance values. In this paper, three machine learning algorithms were evaluated, PCA (principal component analysis), ANN (artificial neural network), SVM (support vector machine). The PCA and forward feature selection algorithms were used to extract features or reduce the dimension of the features. Four comparisons were conducted: NN with PCA, ANN without PCA, SVM with PCA, and SVM without PCA. The results show that the NN with PCA has the best accuracy for the daylighting UDI classification problem. The ANN has an acceptable accuracy for the energy prediction problem.

Climate context of the cold summer of 2014 in Toronto, ON, Canada

Toronto, Ontario, Canada, experienced a cooler summer in 2014, in spite of worldwide record temperatures. In this work, we assess the relative coldness of summer 2014 from a climatological perspective. Using historical temperature data and several thermal metrics, summer 2014 was ranked using three time periods, 1840–2014 (175 years), the full extent of the local instrumental data; 1965–2014, the most recent 50 years; and 1985–2014, the most recent 30 years. For each of the periods, rank within the time period, recurrence interval and average temperature were calculated. Summer of 2014 in Toronto was ranked 118th since 1840 (175 years of data) using the mean daily temperature. The summer of 2014 with an average mean temperature of 20.8 °C was not extreme in nature and is in fact warmer than the average temperature of the time period (19.9 °C). For the more recent time periods, however, the summer was cooler than average but not an extremely cold summer. A monthly analysis showed in particular a cooler July compared to June and August, ranking July 2014 as the 4th coldest July since 1985 whereas June and August were 21st and 10th coldest during the 30-year period, respectively. Recurrence rates did not exceeded 5 years for the seasonal data and 8.3 years for the monthly data. Although the summer of 2014 was cooler than some recent summers, it was not an extreme event such as the Mount Pinatubo-induced cool summer of 1992 which it was explicitly compared to. Finally, an air mass analysis showed that the cooler July of 2014 was the result of a reduced frequency of warm air masses compared to 1992 when there was both a reduction of warm air masses and an increase in colder ones.

3D spatial reconstruction of thermal characteristics in directed energy deposition through optical thermal imaging

A method to analyze and visualize thermal metrics extracted from coaxial thermal images collected during a 3D directed energy deposition is developed as a non-destructive means to assess thermally driven material characteristics and part quality. Standard practice for part qualification in additive manufacturing is through costly post-process non-destructive methods such as 3D digital computer tomography scans, or destructive cross sectional microstructure analysis. The extraction of thermal metrics throughout the build is useful for correlation to build characteristics such as defects or microstructure for process monitoring and control of additive manufacturing processes. The thermal metrics attained from the coaxial images in this work include the thermal gradient at the solidus-to-liquidus region, the maximum temperature in the melt pool, the melt pool area, and the length-to-width ratio of the melt pool, several of which have been correlated to microstructure by other researchers. To demonstrate the proposed methodology, two Ti–6Al–4V L-shaped parts, representative of typical geometric primitives fabricated with this process, were deposited with a 1-bead wide deposition on one leg of the build and 3-bead wide deposition on the second leg of the build. Image filtering techniques were applied in order to distinguish the melt pool solidus-to-liquidus region. Synchronizing thermal images to build location enables generation of a 3D spatial representation of the calculated thermal metrics. Differences in thermal metric values between separate legs of the L-shaped parts express changes in thermal history that can be expected to result in variation in microstructure.

Thermal transient characterization of semiconductor devices with multiple heat sources—Fundamentals for a new thermal standard

The thermal performance of semiconductor devices is most often specified according to JEDEC standards JESD51 1-14 which describes precisely how various steady-state thermal metrics are to be measured. Most of these metrics represent a thermal resistance between the junction of a semiconductor and some reference; e.g. Rth-JA (Junction-to-ambient), Rth-JB (Junction-to-board), or Rth-JC (Junction-to-case). However all of the above thermal metrics characterize the steady-state behavior and have been designed for semiconductors with a single heat source only. While the extension of a stationary thermal resistance Rth-JX to the corresponding transient thermal impedance Zth-JX is straightforward the adaptation of existing standards for the characterization of devices with multiple heat sources is far less obvious. This publication gives an overview on the theoretical framework which allows extending the existing thermal metrics in a compliant way. We demonstrate the method utilized for thermal impedance matrix measurements and show how thermal surroundings affect the thermal relations inside the package.

Using modelled stream temperatures to predict macro‐spatial patterns of stream invertebrate biodiversity

Summary Stream temperature is thought to be a primary determinant of the macro‐spatial distribution of stream biota, but we lack temperature data for most streams. Past research often relied on surrogates, such as altitude, latitude, catchment area (ALCA) and air temperature to study biota–temperature relationships. However, temperature surrogates may not accurately represent the thermal environments experienced by the biota and could thus produce misleading inferences regarding such relationships. In the absence of observations, modelled stream temperature could improve both predictions and interpretations of stream biodiversity patterns. We tested this hypothesis by relating stream benthic invertebrate assemblage structure and composition at 92 reference‐quality streams to ALCA, air temperature, modelled stream temperature and measured stream temperature, that is a progression from a coarse surrogate to directly measured water temperature. Modelled stream temperatures were obtained from a U.S.A.‐wide model developed previously with data from 569 reference‐quality sites. Variation in taxonomic composition, measured with an ordination, was strongly and almost identically associated with both modelled and measured stream temperature, but was less strongly associated with ALCA and air temperature. We also built predictive niche models to assess how choice of thermal metrics affected model performance. Model performance was measured as the precision with which each model predicted the number of taxa at a site (i.e. observed‐to‐expected taxon ratios). Niche models that contained modelled or measured stream temperature were more precise than those based on air temperature and ALCA. In addition, we compared the predicted probabilities of occurrence using niche models based on both modelled and measured stream temperatures. The two produced predicted probabilities of occurrence that were statistically indistinguishable for most (79%) taxa. Finally, we calculated thermal optima for each taxon as the abundance‐weighted average of stream temperature at sites where each taxon occurred. Thermal optima produced with modelled and measured stream temperatures were almost identical. Large‐scale models of stream temperature can be sufficiently accurate and precise to detect temperature‐driven patterns in stream biodiversity and should be useful in predicting the effects of climate change and other human‐caused thermal alterations on stream biodiversity.

Metrics for assessing thermal performance of stormwater control measures

Urban runoff can impact the thermal regime of surface waters and degrade valuable aquatic ecosystems. Some stormwater control measures (SCMs) have been shown to mitigate the effects of thermally-enriched runoff, but previous studies lacked consistency when characterizing the thermal behavior of SCMs. Ecologically-relevant parameters such as maximum outflow temperature, duration of temperatures exceeding thresholds for coldwater species, and thermal load have all been considered in past research. Standard metrics that properly represent the downstream impacts of urban stormwater were needed. This paper evaluated thermal metrics to provide designers and regulators with catchment-scale methods for assessing thermal performance and compliance. It was concluded that multiple metrics must be employed to account for both thermal load and biologically-based reference temperature limits. Metrics for temperature evaluations were broken out by data requirements. When only SCM temperature data are available, event mean temperature estimation appears to be the most rigorous metric. Groundwater temperature may also be employed as a surrogate metric for SCM discharge temperatures if conservative protection of coldwater stream health is desired. When SCM temperature and flow data exist, thermal load reductions should be explored.Efficacy of the low impact development (LID) strategy for temperature mitigation (retaining onsite greater than the 95th percentile storm event) was evaluated using field-collected permeable pavement data. Based on these data, retaining the 95th percentile storm event was determined to be an effective technique for thermal protection of surface waters.However, the most rigorous metrics involve long-term temperature and flow data from local reference streams. The best metric currently available is the uniform continuous above threshold (UCAT) method, in which it is necessary to consider continuous exposure duration when comparing against biological thresholds. These analyses can be tailored to specific species of interest within a targeted ecoregion. Combined with thermal load and mixing analysis in-stream, the UCAT method can provide a real-world estimation of the impacts of development. Additionally, evaluation of mixing zones in-stream should also be employed to adequately assess thermal impacts. However, these methods are the most data intensive.The metrics discussed in this paper can be used to inform new and existing design methodologies for regulating stormwater temperature, duration, and thermal load.

Thermal Metrics for Data Centers: A Critical Review

Thermal management and air distribution performance are assuming a key role for achieving the energy saving and the IT equipment reliability for data centers (DCs). In recent years, to monitor and to control their variation several thermal performance metrics were introduced. This work presents a critical review on the most important thermal indices for DCs currently used. The main formulas and physical models on which they are based were discussed. Moreover, a critical analysis on the main advantages and drawbacks of each metric is carried out.