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At least 253 records · Page 14

Volcanic Contribution to Decadal Changes in Tropospheric Temperature

Despite continued growth in atmospheric levels of greenhouse gases, global mean surface and tropospheric temperatures have shown slower warming since 1998 than previously. Possible explanations for the slow-down include internal climate variability, external cooling influences and observational errors. Several recent modelling studies have examined the contribution of early twenty-first-century volcanic eruptions to the muted surface warming. Here we present a detailed analysis of the impact of recent volcanic forcing on tropospheric temperature, based on observations as well as climate model simulations. We identify statistically significant correlations between observations of stratospheric aerosol optical depth and satellite-based estimates of both tropospheric temperature and short-wave fluxes at the top of the atmosphere. We show that climate model simulations without the effects of early twenty-first-century volcanic eruptions overestimate the tropospheric warming observed since 1998. In two simulations with more realistic volcanic influences following the 1991 Pinatubo eruption, differences between simulated and observed tropospheric temperature trends over the period 1998 to 2012 are up to 15% smaller, with large uncertainties in the magnitude of the effect. To reduce these uncertainties, better observations of eruption-specific properties of volcanic aerosols are needed, as well as improved representation of these eruption-specific properties in climate model simulations.

Atmospheric temperature↗

Cloud-to-Ground Lightning Estimates Derived from SSMI Microwave Remote Sensing and NLDN

Lightning observations are collected using ground-based and satellite-based sensors. The National Lightning Detection Network (NLDN) in the United States uses multiple ground sensors to triangulate the electromagnetic signals created when lightning strikes the Earth's surface. Satellite-based lightning observations have been made from 1998 to present using the Lightning Imaging Sensor (LIS) on the NASA Tropical Rainfall Measuring Mission (TRMM) satellite, and from 1995 to 2000 using the Optical Transient Detector (OTD) on the Microlab-1 satellite. Both LIS and OTD are staring imagers that detect lightning as momentary changes in an optical scene. Passive microwave remote sensing (85 and 37 GHz brightness temperatures) from the TRMM Microwave Imager (TMI) has also been used to quantify characteristics of thunderstorms related to lightning. Each lightning detection system has fundamental limitations. TRMM satellite coverage is limited to the tropics and subtropics between 38 deg N and 38 deg S, so lightning at the higher latitudes of the northern and southern hemispheres is not observed. The detection efficiency of NLDN sensors exceeds 95%, but the sensors are only located in the USA. Even if data from other ground-based lightning sensors (World Wide Lightning Location Network, the European Cooperation for Lightning Detection, and Canadian Lightning Detection Network) were combined with TRMM and NLDN, there would be enormous spatial gaps in present-day coverage of lightning. In addition, a globally-complete time history of observed lightning activity is currently not available either, with network coverage and detection efficiencies varying through the years. Previous research using the TRMM LIS and Microwave Imager (TMI) showed that there is a statistically significant correlation between lightning flash rates and passive microwave brightness temperatures. The physical basis for this correlation emerges because lightning in a thunderstorm occurs where ice is first present in the cloud and electric charge separation occurs. These ice particles efficiently scatter the microwave radiation at the 85 and 37 GHz frequencies, thus leading to large brightness temperature depressions. Lightning flash rate is related to the total amount of ice passing through the convective updraft regions of thunderstorms. Confirmation of this relationship using TRMM LIS and TMI data, however, remains constrained to TRMM observational limits of the tropics and subtropics. Satellites from the Defense Meteorology Satellite Program (DMSP) have global coverage and are equipped with passive microwave imagers that, like TMI, observe brightness temperatures at 85 and 37 GHz. Unlike the TRMM satellite, however, DMSP satellites do not have a lightning sensor, and the DMSP microwave data has never been used to derive global lightning. In this presentation, a relationship between DMSP Special Sensor Microwave Imager (SSMI) data and ground-based cloud-to-ground (CG) lightning data from NLDN is investigated to derive a spatially complete time history of CG lightning for the USA study area. This relationship is analogous to the established using TRMM LIS and TMI data. NLDN has the most spatially and temporally complete CG lightning data for the USA, and therefore provides the best opportunity to find geospatially coincident observations with SSMI sensors. The strongest thunderstorms generally have minimum 85 GHz Polarized Corrected brightness Temperatures (PCT) less than 150 K. Archived radar data was used to resolve the spatial extent of the individual storms. NLDN data for that storm spatial extent defined by radar data was used to calculate the CG flash rate for the storm. Similar to results using TRMM sensors, a linear model best explained the relationship between storm-specific CG flash rates and minimum 85 GHz PCT. However, the results in this study apply only to CG lightning. To extend the results to weaker storms, the probability of CG lightning (instead of the flash rate) was calculated for storms having 85 GHz PCT greater than 150 K. NLDN data was used to determine if a CG strike occurred for a storm. This probability of CG lightning was plotted as a function of minimum 85 GHz PCT and minimum 37 GHz PCT. These probabilities were used in conjunction with the linear model to estimate the CG flash rate for weaker storms with minimum 85 GHz PCTs greater than 150 K. Results from the investigation of CG lightning and passive microwave radiation signals agree with the previous research investigating total lightning and brightness temperature. Future work will take the established relationships and apply them to the decades of available DMSP data for the USA to derive a map of CG lightning flash rates. Validation of this method and uncertainty analysis will be done by comparing the derived maps of CG lightning flash rates against existing NLDN maps of CG lightning flash rates.

Winesett, Thomas↗

Combined Effect of El Nino Southern Oscillation and Atlantic Multidecadal Oscillation on Lake Chad Level Variability Region

In this study, the combined effect of the Atlantic Multidecadal Oscillation (AMO) and El Niño Southern Oscillation (ENSO) on the Lake Chad (LC) level variability is explored. Our results show that the lake level at the Bol monitoring station has a statistically significant correlation with precipitation (R2 = 0.6, at the 99.5% confidence level). The period between the late 1960s and early 1970s marked a turning point in the response of the regional rainfall to climatic drivers, thereby severely affecting the LC level. Our results also suggest that the negative impact of the cold phase of AMO on Sahel precipitation masks and supersedes the positive effect of La Niña in the early the 1970s. The drop in the size of LC level from 282.5 m in the early 1960s to about 278.1 m in 1983/1984 was the largest to occur within the period of study (1900-2010) and coincides with the combined cold phase of AMO and strong El Niño phase of ENSO. Further analyses show that the current warm phase of AMO and increasing La Niña episodes appear to be playing a major role in the increased precipitation in the Sahel region. The LC level is responding to this increase in precipitation by a gradual recovery, though it is still below the levels of the 1960s. This understanding of the AMO-ENSO-rainfall-LC level association will help in forecasting the impacts of similar combined episodes in the future. These findings also have implications for long-term water resources management in the LC region.

ENSO↗

Differences in Pre and Post Vascular Patterning Within Retinas from ISS Crew Members and Head-Down Tilt (HDT) Subjects by VESGEN Analysis

Accelerated research by NASA has investigated the significant risks incurred during long-duration missions in microgravity for Space Flight-Associated Neuro-ocular Syndrome (SANS, formerly known as Visual Impairments associated with Increased Intracranial Pressure, VIIP) [1]. For our study, NASA's VESsel GENeration Analysis (VESGEN) was used to investigate the role of retinal blood vessels in the etiology of SANS/VIIP. The response of retinal vessels to microgravity was evaluated in astronaut crew members pre and post flight to the International Space Station (ISS), and compared to the response of retinal vessels in healthy volunteers to 6deg head-down tilt during 70 days of bed rest (HDTBR). For the study, we are testing the hypothesis that long-term cephalad fluid shifts resulting in ocular and visual impairments are necessarily mediated in part by retinal blood vessels, and therefore are accompanied by structural adaptations of the vessels. METHODS: Vascular patterns in the retinas of crew members and HDTBR subjects extracted from 30deg infrared (IR) Heidelberg Spectralis images collected pre/postflight and pre/post HDTBR, respectively, were analyzed by VESGEN (patent pending). VESGEN is a mature, automated software developed as a research discovery tool for progressive vascular diseases in the retina and other tissues. The multi-parametric VESGEN analysis generates maps of branching arterial and venous trees quantified by parameters such as the fractal dimension (Df, a modern measure of vascular space-filling capacity), vessel diameters, and densities of vessel length and number classified into specific branching generations according to vascular physiological branching rules. The retrospective study approved by NASA's Institutional Review Board included the analysis of bilateral retinas in eight ISS crew members monitored by routine occupational surveillance and six HDTBR subjects (NASA FARU Campaign 11, for example). The VESGEN analysis was conducted in a blinded fashion, with IR retinal images masked to the subject's identity, ophthalmic and clinical characteristics, and to the temporal sequence of image collection. To complete our study, VESGEN results will be analyzed statistically and correlated with other ophthalmic and medical findings. RESULTS: Preliminary results for changes in the pre to post status of vascular patterning in the retinas of crew members and HDTBR subjects are interestingly opposite. By Df and other vascular branching measures, the space-filling capacity of arterial and venous trees decreased in the majority of crew members (11/16 retinas). In contrast, vascular densities increased in HDTBR subjects by the same parameters (6/10 retinas). To conclude the study, biostatistics and medical analyses will be conducted to quantify and draw conclusions about how the changes associated with flight compare to those associated with HDTBR. CONCLUSIONS: Vascular densities appeared to decrease in the retinas of ISS crew members and increase in HDTBR subjects. Differences in arterial and venous response to cephalad fluid shifts induced by ISS and HDTBR may have resulted from a long-duration conditioning phenomenon (for example, 6-month ISS missions compared to 70 days HDTBR), or the presence of gravity in HDTBR compared to microgravity on the ISS. In addition, increased and decreased vessel diameters for Crew Members and HDTBR, respectively, are subject to limits of im

Vascular↗

Predictability of Ocean Heat Content From Electrical Conductance

Ocean heat content (OHC) is a key climate variable that needs to be monitored to know how Earth's energy imbalance is changing, yet observing OHC remains a challenge. The present study examines whether a depth integral of the ocean's electrical conductivity (“conductance”), which may be inferred from both in situ methods and satellite magnetometers over the global ocean, could help monitor OHC. The ocean's electrical conductivity locally depends on temperature, salinity, and pressure, but it is not as well known how the conductance depends on OHC and ocean salt content. By examining the output of an ocean state estimate shown to agree well with observations that have not been assimilated, this study evaluates the fundamental limitations of using perfectly known ocean conductance to predict OHC, rather than the challenges associated with accounting for observational error. It is found that the ocean's conductance and OHC fields are nonlinearly related but nevertheless highly correlated. A statistical framework tends to predict OHC more accurately than ocean salt content from ocean conductance in regions where conductivity is more sensitive to salinity than temperature. The annually (bidecadally) averaged OHC can be predicted from a combination of conductance and depth‐averaged conductivity ocean fields to within nearly 0.1% (1%) error globally and even more accurately in many poorly observed (e.g., ice‐covered) regions. Practical application of this statistical framework to monitor OHC requires examination of the effect of uncertainties in the observed bathymetry and ocean conductance, which vary with application.

Trossman, D. S.↗

Predicting Crew Time Allocations for Lunar Orbital Missions Based on Historical ISS Operational Activities

As the National Aeronautics and Space Administration continues to define candidate architectures for the planned lunar “Gateway”, it will be necessary to have a detailed understanding of how the crew will inhabit, operate, and maintain the spacecraft. The nature of the Gateway vehicle systems configuration and operations will have a direct impact on the scope of work activities required of the crew. Crew work schedules are sensitive to variations in spacecraft architecture, visiting vehicle activities, and logistics operations – particularly within short duration missions as initially planned for the lunar Gateway. These system and operational configurations must be taken into account when planning for crew time availability to conduct science activities on Gateway missions. This paper presents a methodology that is used to predict crew time distributions for lunar Gateway missions, as applied in NASA’s Exploration Crew Time Model (ECTM). The process utilized for evaluating crew time distributions is based on the categorization of all crew activities into a standardized ontology. Historical ISS daily crew timeline data from July 20, 2011 (post STS retirement) to present day was captured via the Operational Planning Timeline Integration System (OPTimIS) database and characterized according to the standardized ontology. This process enabled correlation and statistical analysis of the ISS data according to common mission parameters such as crew size, ECLSS system design, vehicle traffic operations, and logistics delivery operations. The results of the statistical analysis are a set of crew time distributions for each activity category. These distributions are then utilized within the ECTM to examine crew time allocations based on mission parameter inputs, which serve to characterize the Gateway mission configurations. Results for predicted crew time allocations for representative short duration Gateway missions are presented. These results can be used to evaluate crew schedule availability for science and utilization activities. Variations in expected mission architectures and mission operations are accounted for to correct crew time predictions. The analysis is being leveraged to plan utilization capability objectives that are achievable on the Gateway missions, as well as inform the viability of various mission architecture options.

Stromgren, Chel↗

Sea Surface Salinity Retrievals from Aquarius Using Neural Networks

Even though the Sea Surface Salinity (SSS) retrieved from Aquarius are generally very close to in-situ measurements, the level of similarity varies with the region and with the circumstances of the observations (wind speed, sea surface temperature, etc.). SSS is currently retrieved from the brightness temperatures measured by Aquarius and applying the current theoretical model for the propagation and emission of the natural thermal radiation. In this contribution we consider an alternative retrieval approach based on a Neural Network (NN) with the goal of improving the subsets of Aquarius SSS data that are in poorer agreement within-situ measurements. The subset considered here are the SSS retrieved at latitudes higher than 30 ̊. The output of the NN approach are compared against in-situ measurements using four statistical metrics (correlation coefficient, bias, RMSD and 5% trimmed range). The output of the NN and the nominal Aquarius SSS are compared against SSS values from in-situ measurements and from ocean models. From these comparisons it appears that the output of the NN matches the in-situ measurements better than the nominal Aquarius SSS.

Soldo, Yan↗

Aerothermal Analysis of the Dragonfly Titan Entry

The Dragonfly mission will send a rotorcraft lander to the surface of Saturn’s moon Titan as part of the New-Frontiers program. This will be the first spacecraft to land on Titan since the Huygens probe’s descent in January of 2005 and only the second spacecraft to enter Titan’s atmosphere. The Dragonfly entry capsule is significantly larger than the Huygens probe and will experience higher aerothermal environments. This poster will provide an overview of the aerothermodynamic models used in the Dragonfly aeroshell design process. Titan provides a unique entry environment that has several fundamental differences from the environments at the more common entry destinations of Earth and Mars. The lack of atmospheric oxygen significantly reduces heatshield recession (expected to be negligible), which simplifies material response analysis but also reduces the efficiency of the thermal protection system. The atmos-phere is composed of mostly nitrogen and trace amounts of methane. During hypersonic entry this methane dissociates and leads to the formation of the molecule CN, which is known to radiate strongly in the shock layer. Current Dragonfly heating predictions estimate that radiation contributes about 50% of the total heat flux along the forebody and up to 90% on the aftbody, making radiation a key element of aerothermal analysis. To properly address the importance of radiation, a unique radiative-heating correlation was developed that incorporates normal-shock equilibrium chemistry predictions based on work from the Mars 2020 program. These new heating correlations agree well with Computational Fluid Dynamics (CFD) predictions and enable large-scale trajectory analyses by providing rapid heating predictions along candidate trajectories. Dragonfly aerothermal environments are generated with the Data Parallel Line Relaxation (DPLR) finite-volume Navier-Stokes solver alongside the Nonequilibrium Radiative Transport and Spectra (NEQAIR) radiation transport code. DPLR produces shock-aligned flowfields that incorporate the effects of both chemical and thermal nonequilibrium while NEQAIR solves the radiation transport equations along lines-of-sight through the flowfield solutions to predict the radiative heating on the aeroshell. Titan’s atmosphere produces complex thermal and chemical nonequilibria and so classical radiation approximations that extrapolate from a single line-of-sight, such as the Tangent-Slab method, were found to overpredict peak radiative heat fluxes by 10-20%. Therefore, all radiative heating is directly calculated using 3-D transport for both the forebody and aftbody to reduce unnecessary conservatism. A 21-species finite-rate chemistry model, including electrons and ionized species, is used in the CFD to ensure accurate vehicle heating predictions (the level of ionization is particularly for accurate radiative flux predictions). This poster will cover: 1) The models and assumptions used to simulate entry into Titan’s atmosphere, 2) Dragonfly aerothermal engineering correlations alongside statistical heating values, and 3) Driving aerothermal considerations for a Titan entry such as CN formation and radiation-flowfield coupling.

EDL↗

Comparing Two Statistical Models for Low Boom Dose-response Relationships with Correlated Responses

This study compares two statistical modeling approaches to construct summary dose-response curves for low boom community noise surveys. NASA field survey data were used that consist of multiple responses from a survey participant. These data require an approach that accounts for the correlation among repeated annoyance observations from the same participant. A multilevel model accounts for the correlation by allowing estimated parameters to vary with each survey participant. On the other hand, a population average model utilizes generalized estimating equations and accounts for the correlation via a user-specified within-subject correlation structure. A visual comparison of the dose-response curves for these two methods reveals similar results. When comparing specific points along the summary curves, the multilevel model yields more precise confidence bounds than the population average model. The similarity between the summary curves derived from each model lends validity to both approaches for approximating a population representative summary curve.

X-59↗

Comparison of Two Statistical Models for Low Boom Dose-response Relationships with Correlated Responses

This study compares two statistical models to construct summary dose-response curves for low boom community noise surveys. Data from two NASA field surveys are used that consist of multiple responses per survey participant. These data require an approach that accounts for the correlation among repeated annoyance observations from the same participant. A multilevel model accounts for the correlation by allowing estimated parameters to vary with each survey participant. On the other hand, a population average model utilizes generalized estimating equations and accounts for the correlation via a userspecified within-subject correlation structure. A visual comparison of the dose-response curves for these two methods reveals similar results. When comparing specific points along the summary curves, the multilevel model yields more precise confidence bounds than the population average model. The similarity between the summary curves derived from each model lends validity to both approaches for approximating a population representative summary curve, though modeling assumptions may lend favor to the multilevel logistic modeling approach over the population average model.

dose-response↗

A correlational analysis of the effects of changing environmental conditions on the NR atomic hydrogen maser

An extensive statistical analysis has been undertaken to determine if a correlation exists between changes in an NR atomic hydrogen muser's frequency offset and changes in environmental conditions. Data have been acquired over the past 20 months by recording the frequency offset of three NR atomic hydrogen masers along with the relative and absolute humidity, barometric pressure, and ambient temperature of the laboratory in which the masers are maintained. Correlational analyses have been performed comparing barometric pressure, humidity, and temperature with maser frequency offset as functions of time for periods ranging from 5.5 to 17 days. Semi partial correlation coefficients as large as -0.9 have been fond between barometric pressure and maser frequency offset for data covering periods as long as a week. Maser frequency offset and barometric pressure were consistently found to change simultaneously. The correlation between humidity and frequency offset is less predictable, and the resulting semi partial correlation coefficients were usually small when compared with those derived from the relationship between pressure and frequency offset. The time delay between changes in humidity and correlated changes in maser frequency offset was found to vary extensively with no predictable pattern. Analysis of temperature data indicates that, in the most current design, temperature does not significant(y affect maser frequency offset in the laboratory environment. Thus, the results of the analyses disclose a significant statistical correlation between changes in maser frequency offset and changes in barometric pressure. The statistics also reveal some correlation between humidity and frequency offset, bat for reasons to be discussed, the effects of humidity should be considered secondary to the effects of changing barometric pressure.

R. A. Dragonette↗

Electron parameter correlations in high-speed streams and heat flux instabilities

Statistical electron parameter correlations associated with high-speed streams are determined with the aim of identifying one or more locally active solar wind heat flux instabilities. Evidence that points toward local regulation of the heat flux at 1 AU is presented, and the results of a search for special signatures expected from the action of the Alfven, magnetosonic, and whistler flux instabilities are discussed. It is shown that under certain conditions, the whistler mode can be active in regulating the heat flux at 1 AU.

Feldman, W. C.↗

Spatial and temporal variability of VAS radiance measurements by structure and correlation analysis

The statistical structure function analysis presently applied to VISSR Atmospheric Sounder (VAS) measurements has been extended to include time, and yields structure plots in either two spatial dimensions or one spatial dimension and time that indicate three-dimensional measurement variability. The analyses that include time as a coordinate also yield an indication of the mean speed and direction of the analyzed data. Results for three-hourly VAS data indicate that sampling at a high, approximately 1-hour, frequency is required in order to correctly monitor VAS measurements' temporal variability in a way equivalent to high spatial resolution.

Hillger, Donald W.↗

Extreme value statistics analysis of fracture strengths of a sintered silicon nitride failing from pores

Statistical analysis and correlation between pore-size distribution and fracture strength distribution using the theory of extreme-value statistics is presented for a sintered silicon nitride. The pore-size distribution on a polished surface of this material was characterized, using an automatic optical image analyzer. The distribution measured on the two-dimensional plane surface was transformed to a population (volume) distribution, using the Schwartz-Saltykov diameter method. The population pore-size distribution and the distribution of the pore size at the fracture origin were correllated by extreme-value statistics. Fracture strength distribution was then predicted from the extreme-value pore-size distribution, usin a linear elastic fracture mechanics model of annular crack around pore and the fracture toughness of the ceramic. The predicted strength distribution was in good agreement with strength measurements in bending. In particular, the extreme-value statistics analysis explained the nonlinear trend in the linearized Weibull plot of measured strengths without postulating a lower-bound strength.

Chao, Luen-Yuan↗

A technique for generating correlated X-band weather degradation statistics

It is, known that the X-band noise temperature of DSN receivers can go up from 20 K to over 100 K or more, if the air is heavily laden with water vapor, although that is an uncommon occurrence. It is proposed that the DSN furnish flight projects relying on X-band degradation models, one for each DSN Complex. Such models would be in the form of a random process generator, say in an MBASIC program, that would permit the project to generate X-band degradation data with the right autocorrelations for periods of interest to the Projects. The autocorrelation modeling is especially important because bursts of degradation lasting several days can affect data storage and mission sequence design strategy. One approach which works if the degradation statistics obey a half-gaussian law. That is, the random variables are formed by taking the absolute values of another set of random variables, themselves having a Gaussian distribution. The technique then permits the half-gaussian random variables to have given one and two-step correlation coefficients.

Posner, E. C.↗

A statistical approach to analyzing domain dynamics in ferroelectric crystals using X-ray photon correlation spectroscopy

Ferroelectric materials exhibit strong electromechanical coupling, largely influenced by their domain structures. Numerous microstructural studies indicate that smaller domains with higher domain wall density generally enhance domain wall motion, although some inconsistencies have been reported. In this work, we use X-ray photon correlation spectroscopy (XPCS) to probe dynamic response in Pb(Mg 1/3 Nb 2/3 )O 3 -29PbTiO 3 (PMN-29PT) single crystals under applied electric fields. We introduce a two-field correlation approach, adapted from conventional two-time correlation to quantify dynamics. Statistical analysis reveals that both [001]-oriented direct current (DC) and alternating current (AC) poled samples show Poisson-like behavior within specific electric field regions. The DC-poled samples exhibit more frequent domain wall jump events but with smaller amount of decorrelation per jump event, whereas the AC-poled samples show fewer jump events with larger decorrelation per jump event. This observation aligns with the prevalence of 109° domain walls in the AC-poled samples, which contribute to more domain wall motion. These findings provide experimental evidence of collective domain wall motion and establish a direct connection between mesoscale dynamics and electromechanical response.

36 MATERIALS SCIENCE↗

Delta Method Application for the Correlation of IR Detector Thermal Parasitic Loads with Statistically Accurate Results

The Linear Etalon Imaging Spectral Array (LEISA) is a cryogenic IR detector that is passively cooled below 110K. LEISA is part of the L’Ralph instrument, which is going on the Lucy mission, with planned flyby’s of the Trojan asteroids around 5.5 AU. One of the primary thermal challenges is to successfully quantify each significant parasitic heat flow value with statistical certainty.Simulation of flight-like thermal environments and correlation of thermal models is an important part of this challenge, which can be critical for thermally sensitive systems such as cryogenic detectors that are passively cooled. It is common practice during TVAC to achieve several thermal balance points and then to correlate several design variables in order to achieve the closest match to all balance points tested. This approach lends itself to high levels of uncertainty in the correlated values due to the cumulative effect of absolute temperature uncertainty and differences between the sensors used for the measurement. Accuracy can be improved with the use of more accurate sensors, by calibrating all sensors with respect to each other, and by using Zero-Q methodologies, all of which add cost and complexity to the test.The Delta Method uses the difference in temperature caused by the changes in the boundary conditions to calculate heat flows and/or thermal resistances across temperature differentials. This eliminates the problem of high uncertainties with absolute temperature measurements, and yields statistically accurate results down to the sensor resolution of 1mK at < 100K, by taking the sensor’s calibration errors out of the equation. During testing, this method relies on parametric variations around an initial balance point, by varying the boundary conditions of the different parasitic heat sources. The Delta Method, as well as its application on the LEISA thermal test, will be discussed in detail.

Daniel G. Bae↗