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At least 991 records · Page 55

A design perspective on thermal barrier coatings

This technical paper addresses the challenges for maximizing the benefit of thermal barrier coatings for turbine engine applications. The perspective is from a customer's viewpoint, a turbine airfoil designer, who is continuously challenged to increase the turbine inlet temperature capability for new products while maintaining cooling flow levels or even reducing them. This is a fundamental requirement to achieve increased engine thrust levels. Developing advanced material systems for the turbine flowpath airfoils is one approach to solve this challenge; such as high temperature nickel based superalloys or thermal barrier coatings to insulate the metal airfoils from the hot flowpath environment. The second approach is to increase the cooling performance of the turbine airfoil, which enables increased flowpath temperatures and reduced cooling flow levels. Thermal barrier coatings have been employed in jet engine applications for almost 30 years. The initial application was on augmentor liners to provide thermal protection during afterburner operation. However, the production use of thermal barrier coating in the turbine section has only occurred in the past 15 years. The application was limited to stationary parts, and only recently incorporated on the rotating turbine blades. This lack of endorsement of thermal barrier coatings resulted from the poor initial durability of these coatings in high heat flux environments. Significant improvements have been made to enhance spallation resistance and erosion resistance which has resulted in increased reliability of these coatings in turbine applications.

Soechting, Friedrich O.↗

Recent Advances in SMAP RFI Processing

The measurements made by the Soil Moisture Active/Passive (SMAP) mission are affected by the presence of Radio Frequency Interference (RFI) in the protected 1400-1427 MHz band. In SMAP data processing, the main protection against RFI is a sophisticated RFI detection algorithm which flags sub-samples in time and frequency that are contaminated by RFI and removes them before estimating the brightness temperature. This contribution presents two additional approaches that have been developed to address the RFI concern in SMAP. The first consists in locating sources of RFI; once located, it becomes possible to report RFI sources to spectrum management authorities, which can lead to less RFI being experienced by SMAP in the future. The second is a new RFI detection method that is based on detecting outliers in the spatial distribution of measured antenna temperatures.

Radio Frequency Interference↗

Prospects and Limitations of Predicting Fuel Ignition Properties from Low-Temperature Speciation Data

Using chemical kinetic modeling and statistical analysis, we investigate the possibility of correlating key chemical “markers”–typically small molecules–formed during very lean (φ ~ 0.001) oxidation experiments with near-stoichiometric (φ ~ 1) fuel ignition properties. One goal of this work is to evaluate the feasibility of designing a fuel-screening platform, based on small laboratory reactors that operate at low temperatures and use minimal fuel volume. Buras et al. [Combust. Flame2020,216, 472–484] have shown that convolutional neural net (CNN) fitting can be used to correlate first-stage ignition delay times (IDTs) with OH/HO2 measurements during very lean oxidation in low-T flow reactors with better than factor-of-2 accuracy. In this work, we test the limits of applying this correlation-based approach to predict the low-temperature heat release (LTHR) and total IDT, including the sensitivity of total IDT to the equivalence ratio, φ. We demonstrate that first-stage IDT can be reliably correlated with very lean oxidation measurements using compressed sensing (CS), which is simpler to implement than CNN fitting. LTHR can also be predicted via CS analysis, although the correlation quality is somewhat lower than for first-stage IDT. In contrast, the accuracy of total IDT prediction at φ = 1 is significantly lower (within a factor of 4 or worse). Furthermore, these results can be rationalized by the fact that the first-stage IDT and LTHR are primarily determined by low-temperature chemistry, whereas total IDT depends on low-, intermediate-, and high-temperature chemistry. Oxidation reactions are most important at low temperatures, and therefore, measurements of universal molecular markers of oxidation do not capture the full chemical complexity required to accurately predict the total IDT even at a single equivalence ratio. As a result, we find that φ-sensitivity of ignition delay cannot be predicted at all using solely correlation with lean low-T chemical speciation measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TiO2 film properties as a function of processing temperature, volume 3

Thin film TiO2 was produced at 150 C by chemical vapor deposition using hydrolysis of tetraisopropyl titanate. Films were amorphous as grown, but annealing in air caused crystallization, with anatase formed beginning at 350 C and rutile at 700 C. Density and index of refraction increased substantially with increasing anneal temperature, while etch susceptibility in HF and H2SO4 decreased. Comparison with literature data showed two groups of processes. One group yields films having properties that gradually approach those of rutile with increasing process temperature. The other group gives rutile directly at moderate temperatures. Deposition of amorphous film followed by etching and annealing is suggested as a means for pattern definition.

Fitzgibbons, E. T.↗

Improved representation of agricultural land use and crop management for large-scale hydrological impact simulation in Africa using SWAT+

To date, most regional and global hydrological models either ignore the representation of cropland or consider crop cultivation in a simplistic way or in abstract terms without any management practices. Yet, the water balance of cultivated areas is strongly influenced by applied management practices (e.g. planting, irrigation, fertilization, and harvesting). The SWAT+ (Soil and Water Assessment Tool) model represents agricultural land by default in a generic way, where the start of the cropping season is driven by accumulated heat units. However, this approach does not work for tropical and subtropical regions such as sub-Saharan Africa, where crop growth dynamics are mainly controlled by rainfall rather than temperature. In this study, we present an approach on how to incorporate crop phenology using decision tables and global datasets of rainfed and irrigated croplands with the associated cropping calendar and fertilizer applications in a regional SWAT+ model for northeastern Africa. We evaluate the influence of the crop phenology representation on simulations of leaf area index (LAI) and evapotranspiration (ET) using LAI remote sensing data from Copernicus Global Land Service (CGLS) and WaPOR (Water Productivity through Open access of Remotely sensed derived data) ET data, respectively. Results show that a representation of crop phenology using global datasets leads to improved temporal patterns of LAI and ET simulations, especially for regions with a single cropping cycle. However, for regions with multiple cropping seasons, global phenology datasets need to be complemented with local data or remote sensing data to capture additional cropping seasons. In addition, the improvement of the cropping season also helps to improve soil erosion estimates, as the timing of crop cover controls erosion rates in the model. With more realistic growing seasons, soil erosion is largely reduced for most agricultural hydrologic response units (HRUs), which can be considered as a move towards substantial improvements over previous estimates. We conclude that regional and global hydrological models can benefit from improved representations of crop phenology and the associated management practices. Future work regarding the incorporation of multiple cropping seasons in global phenology data is needed to better represent cropping cycles in areas where they occur using regional to global hydrological models.

crop phenology↗

Using data-science approaches to unravel insights for enhanced transport of lithium ions in single-ion conducting polymer electrolyte

Solid polymer electrolytes have yet to achieve the an ionic conductivity > 1 mS/cm at room temperature for realistic applications. This target implies the need to reduce the effective energy barriers of ion transport in polymer electrolytes to around 20 kJ/mol. In this work, we combine information extracted from existing experimental results with theoretical calculations to provide insights into ion transport in single-ion conductors (SICs) with a focus on lithium ion SICs. Through the analysis of temperature-dependent ionic conductivity data obtained from the literature, we evaluate different methods of extracting energy barriers for lithium transport. The traditional Arrhenius fit to the temperature-dependent ionic conductivity data indicates that the Meyer-Neldel rule holds for SICs. However, the values of the fitting parameters remain unphysical. Our modified approach based on recent work (Macromolecules, 56, 15, 6051(2023)), which incorporates a fixed pre-exponential factor, reveals that the energy barriers exhibit temperature dependence over a wide range of temperatures. Using this approach, we identify a series of anions leading to the energy barriers less than 30 kJ/mol, which include trifluoromethane sulfonimide (TFSI), fluoromethane sulfonimide (FSI), and boron-based organic anions. In our efforts to design the next generation of anions, which can exhibit the energy barriers less than 20 kJ/mol, we focused on boron-containing SICs, and performed density functional theory (DFT) based calculations to connect the chemical structures via the binding energy of cation (lithium)-anion pairs with the experimentally derived effective energy barriers for ion transport. Not only have we identified a correlation between the binding energy and the energy barriers, but we also propose a strategy to design new boron-based anions by using the correlation. This combined approach involving experiments and theoretical calculations is capable of facilitating the identification of promising new anions, which can exhibit ionic conductivity $> 1$ mS/cm near room temperature, thereby expediting the development of novel superionic single-ion conducting polymer electrolytes. The published datasets include all the temperature-dependent ionic conductivity collected from the literature with literature DOIs, DFT calculated binding energies, and python scripts to analyze data, construct statistical models, and generate plots.

36 MATERIALS SCIENCE↗

Interfacially Enhanced Superconductivity in Fe(Te,Se)/Bi 4 Te 3 Heterostructures

Realizing topological superconductivity by integrating high-transition-temperature (T C ) superconductors with topological insulators can open new paths for quantum computing applications. Here, a new approach is reported for increasing the superconducting transition temperature $T^{onset}_C$ by interfacing the unconventional superconductor Fe(Te,Se) with the topological insulator Bi–Te system in the low-Se doping regime, near where superconductivity vanishes in the bulk. The critical finding is that the $T^{onset}_C$ of Fe(Te,Se) increases from nominally non-superconducting to as high as 12.5 K when Bi 2 Te3 is replaced with the topological phase Bi 4 Te 3 . Interfacing Fe(Te,Se) with Bi4Te3 is also found to be critical for stabilizing superconductivity in monolayer films where $T^{onset}_C$ can be as high as 6 K. Measurements of the electronic and crystalline structure of the Bi 4 Te 3 layer reveal that a large electron transfer, epitaxial strain, and novel chemical reduction processes are critical factors for the enhancement of superconductivity. This novel route for enhancing T C in an important epitaxial system provides new insight on the nature of interfacial superconductivity and a platform to identify and utilize new electronic phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spatially resolved phase transformation mapping in 410 stainless steel during additive manufacturing visualized via real-time infrared data

Here, in this study, we demonstrate that spatially resolved cooling curves derived from real-time infrared (IR) thermography during additive manufacturing (AM) can capture spatial variations in phase transformation temperatures through cooling curve analysis (CCA). Using this approach, we show that during laser hot-wire deposition of 410 stainless steel (410SS), the martensite start temperature (M s ) evolves dynamically throughout the build. The M s temperature is spatially nonuniform, ranging from 185 °C to 348 °C, with the lowest values toward the build center and higher values toward the upper region of the deposit. In the lower portion of the build, no M s inflection is detected via CCA, consistent with transformation occurring earlier during thermal cycling followed by tempering during subsequent thermal cycles. These trends in M s are corroborated by characterizing the microstructure by electron backscatter diffraction (EBSD). Traditionally, M s is assumed to be constant, and a single interpass temperature is applied during both deposition and residual stress modeling. Our results demonstrate that IR-derived cooling curves provide a route to spatially and temporally resolved transformation temperature tracking for dynamic interpass control and improved residual-stress modeling.

Additive manufacturing↗

High Fidelity CFD Simulations Supporting the KP-FHR

Kairos Power, LLC, is developing its version of the Fluoride-cooled High-temperature Reactor, the KP-FHR. The design uses a pebble bed core with fluoride salt as a coolant. The pebbles used in the KP-FHR have a diameter of 4 cm, with a shell fuel region where TRISO particles are embedded. A Pebble bed core design is adopted by several Gen IV reactors, They boast many benefits, such as fuel integrity, highly efficient heat transfer, and passive safety. However, it is challenging to accurately predict temperature and flow inside a pebble bed. Traditional approaches use the porous media model, which regards the pebble bed as a continuous medium, but with different temperature fields representing different levels, such as the fluid temperature, pebble surface temperature, and pebble center temperature. Empirical heat transfer correlations are adopted to calculate the heat transfer coefficient between different phases. However, empirical correlations are usually validated with experimental data, which usually lacks detail inside the pebble bed. The available experimental data is also generally at a high Reynolds number, which falls outside of the conditions of KP-FHR. Explicit computational fluid dynamics (CFD) simulations of randomly packed pebble beds have only become feasible recently. This is thanks to the rapid development of computational power and scalable algorithms. In this work, we used the Spectral Element Method (SEM) CFD code NekRS to simulate the randomly packed pebble bed in a cylindrical container. NekRS, which is the GPU variant of Nek5000, but refactored to utilize the computational power of GPUs using the OCCA library to run on hybrid architecture high performance computing systems. It was initially developed with the libParamunal library, but truncated and tuned for large-scale turbulence simulation. As a result, the SEM reaches higher precision with the same degrees of freedom by using a high-order Lagrange polynomial basis distributed on Gauss-Lobatto-Legendre quadrature inside each element, compared to lower-order methods, such the Finite Volume Method and Finite Element Method. The report is divided into five parts. We start with a general discussion of the pebble bed reactor, along with a specific investigation into the KP-FHR. The second part presents the numerical methodology. In the third part, we study a modular pebble bed with 1741 pebbles in a container of 7 pebble-diameter radius. Beyond LES simulations done by NekRS, we also leveraged the thermal radiation model in OpenFOAM to study heat transfer under no-forced-flow scenarios. Then, in the fourth part we simulated a pebble bed similar to the size of the Hermes Test Reactor. The total number of pebbles is in these simulations is 34,374. The container radius is 14 pebble-diameters. Finally, the report concludes in part five, with a discussion of future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

Aires, F.↗

Convolution-Based Numerical Solutions of Transient Temperature Fields during Powder Bed Fusion Additive Manufacturing: Theory, Accuracy, and Computational Cost

Powder bed fusion (PBF) additive manufacturing has found numerous applications in the aerospace domain. However, components fabricated via PBF have a complex time-temperature history that significantly impacts subsequent mechanical performance. This study examines convolution-based numerical solutions of transient temperature fields that support simulations involving arbitrary beam shapes and paths during PBF. The convolutional approach is verified through comparisons with analytical solutions of the temperature field. The computational speed and accuracy of the method are assessed through comparisons with other explicit and implicit numerical techniques. In addition, the straightforward translation of the approach from a CPU to a GPU implementation and the resultant performance improvement are presented. The role of the technique in predicting microstructure evolution during PBF (for a greater process-structure-property-performance framework) is also demonstrated. This work supports the development of computational materials methods for understanding and controlling the time-temperature history during PBF.

powder bed fusion↗

Presence of Delocalized Ti 3d Electrons in Ultrathin Single-Crystal SrTiO 3

Strontium titanate (STO), with a wide spectrum of emergent properties such as ferroelectricity and superconductivity, has received significant attention in the community of strongly correlated materials. In the strain-free STO film grown on the SrRuO 3 buffer layer, the existing polar nanoregions can facilitate room-temperature ferroelectricity when the STO film thickness approaches 10 nm. Here we show that around this thickness scale, the freestanding STO films without the influence of a substrate show the tetragonal structure at room temperature, contrasting with the cubic structure seen in bulk form. Further, the spectroscopic measurements reveal the modified Ti-O orbital hybridization that causes the Ti ion to deviate from its nominal 4+ valency (3d o configuration) with excess delocalized 3d electrons. Additionally, the Ti ion in TiO 6 octahedron exhibits an off-center displacement. The inherent symmetry lowering in ultrathin freestanding films offers an alternative way to achieve tunable electronic structures that are of paramount importance for future technological applications.

36 MATERIALS SCIENCE↗

High-entropy 1D halide perovskite piezoelectrics found by megalibrary synthesis and rapid nonlinear optical screening

Piezoelectric molecular crystals offer excellent compositional and structural tunability and sustainable processability. However, their discovery is slow, primarily due to the serial synthesis and screening processes used. Here, we report an approach that combines massively parallel megalibrary synthesis with scanning second harmonic generation (SHG) microscopy for rapid screening of piezoelectric molecular crystals. Megalibraries consisting of more than 1,000,000 compositionally distinct but positionally encoded TMCM x TMA (1–x) Cd y Pb (1–y) ClzBr (3–z) (TMCM: trimethylchloromethylammonium, TMA: tetramethylammonium; 0 ≤ x ≤ 1, 0 ≤ y ≤ 1, 0 ≤ z ≤ 3) nanocrystals were synthesized. The megalibraries were rapidly screened by SHG microscopy to identify notable noncentrosymmetric structures, which were then tested for piezoelectricity, facilitating discovery of a high-entropy noncentrosymmetric material with a large d 33 (TMCM 0.75 TMA 0.25 Cd 0.75 Pb 0.25 Cl 1.5 Br 1.5 , 42.8 picocoulombs per newton). Furthermore, this approach enabled systematic investigation of the Curie temperature (T C )–composition relationship in the TMCMCdCl z Br (3–z) system, facilitating reverse design of materials with targeted T C . Our work establishes a powerful approach to accelerate the discovery and design of unusual piezoelectrics for next-generation electronics and optics.

Li, Jun [Northwestern University, Evanston, IL (Un↗

Damage Accumulation and Failure of Plasma-Sprayed Thermal Barrier Coatings under Thermal Gradient Cyclic Conditions

Thermal barrier coatings will be more aggressively designed to protect gas turbine engine hot-section components in order to meet future engine higher fuel efficiency and lower emission goals. A fundamental understanding of the sintering and thermal cycling induced delamination of thermal barrier coating systems under engine-like heat flux conditions will potentially help to improve the coating temperature capability. In this study, a test approach is established to emphasize the real-time monitoring and assessment of the coating thermal conductivity, which can initially increase under the steady-state high temperature thermal gradient test due to coating sintering, and later decrease under the thermal gradient cyclic test due to coating cracking and delamination. Thermal conductivity prediction models have been established for a ZrO2-(7- 8wt%)Y2O3 model coating system in terms of heat flux, time, and testing temperatures. The coating delamination accumulation is then assessed based on the observed thermal conductivity response under the combined steady-state and cyclic thermal gradient tests. The coating thermal gradient cycling associated delaminations and failure mechanisms under simulated engine heat-flux conditions will be discussed in conjunction with the coating sintering and fracture testing results.

Zhu, Dongming↗

DC Cryogenic Modeling of Open-Source SkyWater 130 nm MOSFETs at 77 K Using BSIM4

Cryogenic applications in high-energy physics (HEP) demand reliable, low-power CMOS electronics capable of operating at liquid nitrogen temperatures (77 K). The open-source SkyWater 130nm (SKY130) CMOS process has previously been shown to operate at temperatures as low as 4 K making it a promising candidate for HEP applications. In this work, we characterize and model SKY130 low-threshold voltage transistors at 77 K, which is a temperature commonly used in modeling applications for liquid argon detectors. DC characteristic measurements were performed at both room temperature and liquid nitrogen temperature. We created a cryogenic modeling approach to produce a SPICE-compatible, isothermal BSIM4-based model for select transistor sizes at 77 K. The resulting model agrees with data at 77 K with an average error on the order of 20% (relative RMS) and shows no dependence on drain voltage. Due to the open-source nature of SKY130, we have made our models publicly available on Github. We hope this work will continue the trend for democratizing circuit design at cryogenic temperatures in high-energy physics by enabling open access to accurate cryogenic CMOS device models at 77 K.

Beall, F. [Texas U., Arlington]↗

Lithium's low-temperature phase transitions: Insights into quantum lattice dynamics and superconductivity

The large lattice dynamics of lithium, driven by its low atomic mass, results in energetically similar structures and significant isotope effects under pressure, posing challenges to current theoretical models. Above 20 GPa and at low temperatures, lithium's electronic properties deviate from simple metallic behavior, with superconductivity emerging in a complex, pressure-dependent manner, alongside an unusual isotope effect. The structural phases of 7 Li reported under these conditions are inconsistent across studies, and the structures of 6 Li remain unexamined. These gaps limit our understanding of the effects of pressure on lithium's electronic properties and the role of quantum lattice effects on its structural behavior under pressure. Here, we integrate experimental and theoretical approaches to investigate the low-temperature structural phase boundaries in lithium isotopes. We map the structural phase diagram of 7 Li from 5 to 55 GPa and 15–75 K, identifying the sequence fcc → ℎ⁡R⁢1 → cI16. A pronounced isotope effect is observed, with 6 Li shifting the fcc → ℎ⁡R⁢1 phase boundary to lower pressures at 15 K. Density functional theory calculations further clarify how these structural changes affect superconducting properties, particularly emphasizing the role of the fcc → ℎ⁡R⁢1 transition in lithium's superconductivity. Furthermore, our findings offer insights into the unique behavior of lithium isotopes under pressure.

36 MATERIALS SCIENCE↗

Impact of Mineral Aerosol on TOVS Temperature and Moisture Retrievals

Mineral aerosols can absorb significant radiation in the infrared spectrum. Consequently, there may be errors in TIROS Operational Vertical Sounder (TOVS) retrieved temperature and moisture profiles in regions of heavy dust loading. We first investigate the potential error in the temperature retrievals and secondly attempt to account for radiative effects of the dust in retrievals. Information on the dust concentrations and size distribution is from the Goddard Chemistry Aerosol Transport model (GOCART). Aerosol optical parameters are calculated from mie scattering theory assuming a composition of pure illite. We used the cloud-clearing DAO TOVS retrieval system of Joiner and Rokke (2000). It is incorporated into the Data Assimilation Office (DAO) Finite Volume Data Assimilation System (NDAS). The advantage of this approach is that the first guess temperature profile used in the TOVS retrieval are forecasted temperatures from the previous assimilated time period. The operational DAO fvDAS was run for 10 days during June 2001 during a period of dust outbreaks off the coast of Africa over the Atlantic. The observed minus the forecast (O-F) brightness temperature at each TOVS channel is a measure of the accuracy of the retrieval. Since there was no account of dust during this operational run, a dependence of O-F on the estimated atmospheric dust concentrations from GOCART indicates that the dust is contaminating the TOVS retrievals. Channels that measure the surface temperature, lower tropospheric temperature and moisture show this dependence. There are errors in the retrieved brightness temperature of a half a degree or more during heavy dust loading conditions. The forecasted brightness temperature is always greater than the observed value. The radiative transfer module used in the DAO TOVS retrieval system was modified to account for dust. We calculate the sensitivity of the brightness temperature of the TOVS channels to the dust concentrations in GOCART assuming pure illite. For most channels the observed relationship between O-F and dust concentrations in GOCART is consistent with these calculated sensitivities. The fvDAS run was repeated using the modified DAO TOVS retrieval system that accounts for dust. Preliminary results from this run show that there are significant effects on the retrieved surface temperature and tropospheric moisture.

Weaver, Clark↗

TRASYS form factor matrix normalization

A method has been developed for adjusting a TRASYS enclosure form factor matrix to unity. This approach is not limited to closed geometries, and in fact, it is primarily intended for use with open geometries. The purpose of this approach is to prevent optimistic form factors to space. In this method, nodal form factor sums are calculated within 0.05 of unity using TRASYS, although deviations as large as 0.10 may be acceptable, and then, a process is employed to distribute the difference amongst the nodes. A specific example has been analyzed with this method, and a comparison was performed with a standard approach for calculating radiation conductors. In this comparison, hot and cold case temperatures were determined. Exterior nodes exhibited temperature differences as large as 7 C and 3 C for the hot and cold cases, respectively when compared with the standard approach, while interior nodes demonstrated temperature differences from 0 C to 5 C. These results indicate that temperature predictions can be artificially biased if the form factor computation error is lumped into the individual form factors to space.

Tsuyuki, Glenn T.↗