Thesis Proposal: Sensitivity analysis of temperature variations in the MCNP model of the ACRR Fuel during operations.
Abstract not provided.
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Abstract Snow water equivalent (SWE), temperature, and precipitation biases and trends are evaluated in the atmosphere‐land simulations of the Energy Exascale Earth System Model version 1 (E3SMv1) in comparison to the Community Earth System Model version 2 (CESM2) and two other models using the ground measurement‐based University of Arizona (UA) snow product. SWE, temperature, and precipitation biases are highest in magnitude in the Western contiguous United States (CONUS). SWE errors are attributed to temperature and precipitation through multiple linear regressions of normalized errors, the coefficients of which represent the sensitivities to temperature and precipitation errors. SWE errors are more sensitive to temperature errors throughout the CONUS. Model SWE and temperature trends are generally opposite from UA product trends in the Western CONUS. SWE trend errors are also attributed to temperature and precipitation trend errors using multiple linear regressions of normalized trend errors. SWE trend errors are more sensitive to those of precipitation at higher elevations (>1,500 m) in the Western CONUS in these simulations. Thus, the sensitivity to temperature and precipitation differ for SWE errors and its trend errors. Furthermore, the SWE trend errors are more sensitive to temperature and precipitation in the atmosphere‐ocean coupled simulations in which the atmosphere‐land is coupled to an active ocean model. These results suggest that both errors in simulated temperature and precipitation contribute to SWE errors.
For traditional overhead transmission lines, the maximum allowable conductor operating temperature on ASCR, AAC, or AAAC lines for determining the static line ratings can be quite low, typically well under 100 C. At these low temperatures, the primary driver for determining static line ratings are assumptions made about the wind speed and direction and the ambient temperature. Assumptions for solar loading and emitted thermal radiation, driven by line emissivity and absorptivity, are secondary factors, and only provide small changes to the static ratings. However, when considering newer high temperature conductors such as ACSS, ACCR, ZTACIR, and ACCC® the maximum allowable conductor temperatures can be significantly higher, up to 250° C. This higher temperature shifts the importance of the emissivity assumptions of the overhead transmission line, due to the nature of the T4 dependence of the radiative heat loss compared to the T1 dependence of the convective heat loss, as well as shifting the dependency on local wind conditions. Typical assumptions in the United States for the emissivity/absorptivity of overhead transmission lines in determining the static ratings are to use a value of 0.5 for both parameters or set a value in the range of 0.7 to 0.9. Recent experimental tests at EPRI have shown that higher emissivity aging assumptions may not be valid in some regions of the US, and that actual values may be much lower (0.25-0.45) than older studies have predicted (0.8-0.9). Here, the assumptions of different US Regional Transmission Operators (RTOs) and different utilities within RTOs are examined for the static ratings for traditional lower operating temperatures up to 100° C as well as with the higher maximum temperature conductors associated with newer conductor designs at 250° C. The sensitivity of the static ratings is examined at both lower and higher temperature conductors with respect to overhead line emissivity and absorptivity, wind speed, wind direction, and solar loading, and ambient temperature. It is shown that the effects of the conductor absorptivity, solar flux and ambient temperature on the static rating are increased when the transmission line has a lower maximum conductor temperature. The effects of the conductor emissivity, wind direction and wind speed have increased effects on the static rating when the transmission line has a higher maximum conductor temperature. In addition, example weather data is used to calculate the conductor temperature with different line emissivity and absorptivity assumptions. This shows the effect of assumptions made for emissivity only has a minor impact for low temperature lines, but for high temperature transmission lines can cause a 150-200° C temperature swing.
We report a fiber-optic sensor configuration with a cascaded fiber Bragg grating (FBG) and a silicon Fabry-Perot interferometer (FPI) for simultaneous measurement of temperature and strain. The sensor is composed of a 5 mm FBG on a single mode fiber and a 100μm thick silicon FPI attached to the tip of the optical fiber. The FBG is surface mounted on the host structure, and the FPI tip is suspended. Due to the stress-free, cantilever configuration, the silicon FPI is insensitive to strain, but sensitive to temperature with a sensitivity much higher than the FBG due to the large thermo-optic coefficient of silicon. The sensor is tested from room temperature to 100°C with varying strain up to ∼150με. The silicon FPI provides high temperature sensitivity of 89 pm/°C unaffected by strain. Since the FBG is attached to the host structure, it is affected by both thermal and mechanical strain; the sensitivity of these was experimentally obtained 32 pm/°C and 1.09 pm / με, respectively. Interrogated with a broadband light source and a high-speed spectrometer, the sensor shows temperature and strain resolutions of 1.9 × 10 −3 °C and 0.042 με, respectively. Here, due to the small size, enhanced sensitivity, and high resolution, this cascaded FBG-FPI sensor can be used in applications where accurate measurement of temperature and strain is required.
We report the corrosion behavior and tensile properties of oxide dispersion strengthened (ODS) FeCr, FeCrAl, FeCrAlMo steels and 316H stainless steel were evaluated after 1000 h at 700 °C in static sodium with and without an oxygen getter (Zr foil). Without Zr foil to getter the dissolved oxygen in the liquid sodium, combined oxidation (formation of Cr, Fe-rich or Al-rich oxides) and dissolution of the studied materials was observed. For the ODS FeCr, Cr- and Fe-rich oxide formation and dissolution induced Cr depletion in the underlying alloy and led to the formation of laves phases that were observed to be detrimental to the room temperature tensile properties. For ODS FeCrAlMo and FeCrAl Al-rich oxide formation and dissolution resulted in Al depletion in the underlying alloys but did not impact tensile properties at room temperature. For 316H temperature induced sensitization combined with oxidation decreased room temperature tensile properties. With Zr foil added as oxygen getter, roughened surfaces and Al depletion profiles suggested the dissolution of ODS FeCr and FeCrAl into the liquid sodium while limited dissolution was observed for ODS FeCrAlMo and 316H. For the 316H and ODS FeCrAlMo steels, precipitates were formed at the grain boundaries after exposure. Tensile properties of ODS FeCr, FeCrAl and FeCrAlMo were not affected by the 1000 h corrosion exposure with Zr foil added to the sodium but for 316H temperature-induced grain boundary sensitization negatively affected the tensile properties.
Abstract Almost all current climate models simplify the ocean surface albedo (OSA) by assuming the reflected solar energy without the ocean interior contribution. In this study, an improved ocean surface albedo scheme is incorporated into the Community Earth System Model version 2 (CESM2) to assess the sensitivity of Arctic surface temperature to including ocean interior reflectance to the OSA. Fully coupled CESM2 simulations with and without ocean interior reflectance are subsequently performed, we focus on the analysis of Arctic surface temperature responses. Incorporating ocean interior reflectance increases absorbed solar radiation and warms the ocean, enhancing seasonal heat storage and release across the Arctic Ocean, and increasing sea ice reduction and positive climate feedbacks that elevates Arctic surface temperature. Seasonal variations in air‐surface temperature differences induce changes in turbulent heat flux patterns, concurrently modifying dynamic advection and moisture processes that affect boundary layer humidity and low clouds, especially in winter. Based on partitioning physical processes in the thermodynamic energy equation, surface air warming is induced primarily through positive heating anomalies of vertical advection, latent heat release, and longwave radiative forcing. Through an examination of the surface energy budget, skin temperature warming is driven predominantly by increased downward longwave radiation, positive surface albedo feedback in summer, and increased conductive heat transport from the ocean particularly in winter. Significant effects of ocean interior reflectance on the Arctic Ocean, including sea surface warming and sea ice reduction, justify the importance of ocean interior reflectance in climate models for better understanding of ongoing Arctic climate changes.
Abstract The sensitivity of urban canopy air temperature ( T a ) to anthropogenic heat flux ( Q A H ) is known to vary with space and time, but the key factors controlling such spatiotemporal variabilities remain elusive. To quantify the contributions of different physical processes to the magnitude and variability of Δ T a / Δ Q A H (where Δ represents a change), we develop a forcing-feedback framework based on the energy budget of air within the urban canopy layer and apply it to diagnosing Δ T a / Δ Q A H simulated by the Community Land Model Urban over the contiguous United States (CONUS). In summer, the median Δ T a / Δ Q A H is around 0.01 K W m − 2 − 1 over the CONUS. Besides the direct effect of Q A H on T a , there are important feedbacks through changes in the surface temperature, the atmosphere–canopy air heat conductance ( c a ), and the surface–canopy air heat conductance. The positive and negative feedbacks nearly cancel each other out and Δ T a / Δ Q A H is mostly controlled by the direct effect in summer. In winter, Δ T a / Δ Q A H becomes stronger, with the median value increased by about 20% due to weakened negative feedback associated with c a . The spatial and temporal (both seasonal and diurnal) variability of Δ T a / Δ Q A H as well as the nonlinear response of Δ T a to Δ Q A H are strongly related to the variability of c a , highlighting the importance of correctly parameterizing convective heat transfer in urban canopy models.
Abstract. As offshore wind farm development expands, accurate wind resource forecasting over the ocean is needed. One important yet relatively unexplored aspect of offshore wind resource assessment is the role of sea surface temperature (SST). Models are generally forced with reanalysis data sets, which employ daily SST products. Compared with observations, significant variations in SSTs that occur on finer timescales are often not captured. Consequently, shorter-lived events such as sea breezes and low-level jets (among others), which are influenced by SSTs, may not be correctly represented in model results. The use of hourly SST products may improve the forecasting of these events. In this study, we examine the sensitivity of model output from the Weather Research and Forecasting model (WRF) 4.2.1 to different SST products. We first evaluate three different data sets: the Multiscale Ultrahigh Resolution (MUR25) SST analysis, a daily, 0.25∘ × 0.25∘ resolution product; the Operational Sea Surface Temperature and Ice Analysis (OSTIA), a daily, 0.054∘ × 0.054∘ resolution product; and SSTs from the Geostationary Operational Environmental Satellite 16 (GOES-16), an hourly, 0.02∘ × 0.02∘ resolution product. GOES-16 is not processed at the same level as OSTIA and MUR25; therefore, the product requires gap-filling using an interpolation method to create a complete map with no missing data points. OSTIA and GOES-16 SSTs validate markedly better against buoy observations than MUR25, so these two products are selected for use with model simulations, while MUR25 is at this point removed from consideration. We run the model for June and July of 2020 and find that for this time period, in the Mid-Atlantic, although OSTIA SSTs overall validate better against in situ observations taken via a buoy array in the area, the two products result in comparable hub-height (140 m) wind characterization performance on monthly timescales. Additionally, during hours-long flagged events (< 30 h each) that show statistically significant wind speed deviations between the two simulations, both simulations once again demonstrate similar validation performance (differences in bias, earth mover's distance, correlation, and root mean square error on the order of 10−1 or less), with GOES-16 winds validating nominally better than OSTIA winds. With a more refined GOES-16 product, which has been not only gap-filled but also assimilated with in situ SST measurements in the region, it is likely that hub-height winds characterized by GOES-16-informed simulations would definitively validate better than those informed by OSTIA SSTs.
Policy, business, finance and civil society stakeholders are increasingly looking to compare future emissions pathways across both their associated physical climate risks stemming from increasing temperatures and their transition climate risks stemming from the shift to a low-carbon economy. Herein, we present an integrated framework to explore near-term (to 2030) transition risks and longer-term (to 2050) physical risks, globally and in specific regions, for a range of plausible greenhouse gas emissions and associated temperature pathways, spanning 1.5–4 °C levels of long-term warming. By 2050, physical risks deriving from major heatwaves, agricultural drought, heat stress and crop duration reductions depend greatly on the temperature pathway. By 2030, transition risks most sensitive to temperature pathways stem from economy-wide mitigation costs, carbon price increases, fossil fuel demand reductions and coal plant capacity reductions. Considering several pathways with a 2 °C target demonstrates that transition risks also depend on technological, policy and socio-economic factors.
Data for figures contained in "Sensitivities of time-dependent temperature profile predictions for NSTX with the Multi-Mode Model"
Predicting the effects of microstructure on high-temperature creep responses of steel components is critical to minimize the risks of failure and maximize economic viability in the energy sector. In this research, a recently developed advanced mechanistic constitutive model is employed to study the effect of microstructure on the creep responses and to rationalize experimentally reported variability in the performances of grade-91 alloy. Hundreds of experimental creep tests from the literature are used to assess the predictability of the model. The model proposed is shown to accurately predict the steady-state creep rates and also the less commonly considered, yet important, primary-to-secondary transients for a wide range of creep conditions. Further, the model is capable of extrapolating the creep response of grade 91 alloy even outside of the calibration regime. Using this model, the roles of initial microstructure described in terms of grain size, dislocation density, and precipitate content, on the creep responses are investigated. The effect of initial microstructure on the steady-state creep rates and creep-strain is found to vary with stress and temperature. Grain size plays a significant role in the low-stress creep, where the diffusional creep is dominant. On the other hand, the effects of dislocation densities and precipitate content are significant in the dislocation-plasticity-dominated high-stress and temperature regimes. Furthermore, by comparing model predictions against a large experimental creep database, it is found that variability in the creep responses can be rationalized on the basis of differences in the initial microstructure. Overall, this work provides a robust pathway for microstructure-aware engineering design, verification, and validation of metallic components for energy applications.
This report describes thermal modeling done to understand the effects of a hypothetical loss of backfill to a spent fuel storage canister. A NAC MAGNASTOR system was analyzed using STAR-CCM+ and COBRA-SFS at various heat loads, helium pressures, and air environments. When helium was lost later in life the results showed no safety impact to the thermal performance of the cask system and fuel cladding. However, there were other results of interest from this study. The potential to detect helium leaks using external temperature measurement was considered and found to be a potential area for future technology development. The other major result of interest was the significant change in flow velocities with an air environment. This data will be useful in understanding the potential impacts of a breached canister.
IEEE/CIGRE standards provide a base for overhead transmission line ratings Steady State Ampacity industry standard for Static Ratings using conservative environmental assumptions Measurement of many types of sensors provide a possibility to provide more capacity as a time varying capability Direct sensors of line temperature, tension, or sag provide critical, location specific information. Require complex transformation to determine line ampacity rating Are direct measurements sensors placed at key location(s)? Testing and careful calibration of sensors required Need to understand impact of uncertainties on sensors/measurements/ and forecasts
This article presents a systematic study of Pu(IV) absorbance spectral features as a function of temperature to develop an understanding of this parameter’s effect on chemometric models that can be used as online monitoring tools to support nuclear processing. The descriptive and predictive models that provide real-time feedback of these processes are usually constructed with data collected in conditions typical of a laboratory environment, which can differ drastically from a processing environment. To assess the impact of temperature on Pu(IV) absorbance spectra, 11 samples of Pu(IV) were synthesized with varying HNO 3 concentrations ranging from 0.6 to 9.5 M and heated between 15 and 45 °C. Ultraviolet (UV)–visible (vis)–near-infrared (NIR) absorption spectra collected at different HNO 3 concentrations and temperatures revealed that features associated with Pu(IV) are sensitive to temperature at all HNO 3 concentrations and that changes in features depend on HNO 3 concentration. The contributions of temperature and HNO 3 concentration to variation in Pu(IV) spectral features were evaluated using the principal component analysis of spectra that were baseline-corrected with an asymmetric least-squares method. Furthermore, predictive modeling for HNO 3 concentration with partial least-squares regression of UV–vis–NIR spectra highlighted the importance of accounting for temperature in the calibration set to optimize model performance. This methodology constitutes a new, systematic approach to account for the effect of temperature on the absorption spectra of metal ions and is useful for process monitoring applications in many industries.
Sandia National Laboratories has tested and evaluated two variations of a new model of infrasound sensor, the Hyperion 5313A and 5119A. The purpose of this infrasound sensor evaluation is to measure the performance characteristics in such areas as power consumption, sensitivity, full scale, self-noise, dynamic range, response, passband, sensitivity variation due to changes in static pressure and temperature, and sensitivity to vertical acceleration. The Hyperion infrasound sensors are being evaluated for potential use in the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO).
Sandia National Laboratories has tested and evaluated the performance of the following five models of low-cost infrasound sensors and sensor packages: Camas microphone, Gem Infrasound Logger, InfraBSU sensor, Raspberry Boom, and the Samsung S10 smartphone utilizing the Redvox app. The purpose of this infrasound sensor evaluation is to measure the performance characteristics in such areas as power consumption, sensitivity, self-noise, dynamic range, response, passband, linearity, sensitivity variation due to changes in static pressure and temperature, and sensitivity to vertical acceleration. The infrasound monitoring community has leveraged such sensors and integrated packages in novel ways; better understanding the performance of these units serves the geophysical monitoring community.
Sandia National Laboratories has tested and evaluated an updated version of the MB3a infrasound sensor, designed by CEA and manufactured by SeismoWave. The purpose of this infrasound sensor evaluation is to measure the performance characteristics in such areas as power consumption, sensitivity, full scale, self-noise, dynamic range, response, passband, sensitivity variation due to changes in barometric pressure and temperature, and sensitivity to acceleration. The MB3a infrasound sensors are being evaluated for use in the International Monitoring System (IMS) of the Preparatory Commission to the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO).