Search NASA⌕ Search

SEARCH · Search NASA

Results for “thermal statistical models”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Bulk and position-specific isotope geochemistry of natural gases from the Late Cretaceous Eagle Ford Shale, south Texas

Here, a dataset of bulk and position-specific isotope compositions of shale gases from the Late Cretaceous Eagle Ford Shale, south Texas is reported. The chemical and bulk isotopic compositions of the seven samples in this study and those available from the literature show that across the play, produced natural gas from the Eagle Ford Shale preserves a wide range of gas compositions (wetness, ~5 to >90%) and δ 13 C values of C 1 –C 3 . The depth profiles of the isotopic compositions suggest that the western region of the Eagle Ford Shale deposit had experienced as much as 700–800 m of uplift-erosion or gas migration. The timing of and lost-gas fractions by gas expulsion events very likely affected their gas compositions and bulk isotope compositions. Some deep (>3000–3500 m), matured (%Ro > 1.5) gases with heavy δ 13 C(C 1 –C 3 ) values indicate significant loss (>50%) of the early-stage gases. For the position-specific isotope deviations of propane, the ΔC 2-1 values of the five samples show small decrease with well depths, while the ΔH 2-1 values have a general increasing trend. Although some samples fall very close to the equilibrium model trajectories with reasonable calculated temperatures (138–148 °C), the position-specific isotope compositions of propane from the Eagle Ford Shale gases are likely results of thermal cracking of various organic molecules within the source rocks, which have different activation energy for cracking and non-statistical distributions of C/H isotope within them.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Big-data Efficient and Automated Science Transfer (BEAST): An Open-Source Software Architecture for Arc Jet Data Management, Modeling, and Automation

Big-data Efficient and Automated Science Transfer (BEAST) was conceived to address the existing ground testing data management of the NASA Ames arc jet facilities (e.g., manually entered Excel files and USB drive data transfers). These data management practices were seen as a choke point for future thermal protection system (TPS) development as they limit statistical tracking, resolution of diagnostics, coordination between video/time series, data throughput, and data processing speed/efficiency. Consequently, BEAST was developed to provide a new data infrastructure with streamlined data collection, processing, transfer, and analysis. This new framework also seeks to implement the FAIR principles of data stewardship: Findable, Accessible, Interoperable, and Reusable. The BEAST framework is based on a combination of the Python Django web framework and the Python data stack to provide a monolithic, open-source platform for data management, automation, and machine learning. This architecture was chosen for maintainability and scalability for a small, in-house development team. This paper will describe the application framework, deployment, and discuss the benefits and future plans for the system.

Data management↗
NASA NTRSDate not supplied

Big-data Efficient Automated Science Transfer (BEAST): an open-source software architecture for arc jet data management, modeling, and automation

Big-data Efficient and Automated Science Transfer (BEAST) was conceived to address the existing ground testing data management of the NASA Ames arc jet facilities (e.g., manually entered Excel files and USB drive data transfers). These data management practices were seen as a choke point for future thermal protection system (TPS) development as they limit statistical tracking, resolution of diagnostics, coordination between video/time series, data throughput, and data processing speed/efficiency. Consequently, BEAST was developed to provide a new data infrastructure with streamlined data collection, processing, transfer, and analysis. This new framework also seeks to implement the FAIR principles of data stewardship: Findable, Accessible, Interoperable, and Reusable. The BEAST framework is based on a combination of the Python Django web framework and the Python data stack to provide a monolithic, open-source platform for data management, automation, and machine learning. This architecture was chosen for maintainability and scalability for a small, in-house development team. This paper will describe the application framework, deployment, and discuss the benefits and future plans for the system.

Data management↗
NASA NTRS2012

Towards the Handing of Cloud-Affected Infrared Radiances in the GSI

In the gridpoint statistical interpolation (GSI) data assimilation algorithm, only thermal infrared measurements determined to be uncontaminated by clouds are assimilated. Using this approach, typically only 19-29% of footprints are deemed to have no cloud affects through the measured spectra. This study will discuss the efforts underway at the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center, in conjunction with the Joint Center for Satellite Data Assimilation (JCSDA), to actively assimilate these morecomplicated observations by using a graybody assumption. In the GSI, cloud top pressure and effective cloud amount are retrieved concurrently using a minimum residual method. This study will address the limitations and advantages of the technique and the modifications underway to the assimilation system to incorporate those two parameters into the radiative transfer forward operators and TL/AD calculations. Furthermore, it will explain the efforts underway to incorporate these parameters into the control vector so that they can be altered variationally as part of the minimization.

McCarty, William↗
DOE OSTI2024

Stochastic Optimization and Uncertainty Quantification of Natrium-based Nuclear-Renewable Energy Systems for Flexible Power Applications in Deregulated Markets

Rapid integration of variable renewable energy sources (VRES) has made modeling and stochastic optimization of hybrid energy systems crucial for studying their long-term performance and viability. However, most studies have focused on just historical data, which may be unreliable for capturing short-term fluctuations, rare events, and long-term patterns of energy demand, price, and the variability of renewable energy sources. For this study, optimal synthetic time series models were developed using Wasserstein distance. The models were validated by comparing the key statistical measures against those of the historical data. They were then used to optimize the integrated Natrium-style advanced energy systems and their long-term (30 years) economics. The stochastic model performs bi-level optimization to find the optimal sizes for the balance of plant and thermal energy storage, while also optimizing energy dispatch to achieve the maximum net present value. In studies of two deregulated markets (California ISO and the Electric Reliability Council of Texas), the integrated Natrium-style system performed better in CAISO than in ERCOT, given higher and more consistent electricity prices during peak-demand periods. The potentially enlarged cost associated with the variable operation and maintenance of the TES system also plays a significant role in driving the system sizing, thus its impacts on the system are investigated in detail through comparison against a baseline case. The study also finds that the bi-level optimization results based on stochastic gradient descent closely match the grid search results. The uncertainty quantification of the stochastic signals provides further NPV-related insights and probability distributions for the case studies. The normal standard error of the mean of NPV for the case with and without TES VOM for CAISO were found to be 7.73M (plus-minus sign) 1.09M USD and 104.99M (plus-minus sign) 1.25M USD, respectively based on a 95% confidence. Given the relatively small NPV variance based on 150 samples, the analysis affords the most robust possible prediction of the techno-economic performance of the integrated Natrium-style energy systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Measurement of directed flow in Au + Au collisions at $\sqrt{s{NN}}$ = 19.6 and 27 GeV with the STAR event plane detector

In heavy-ion collision experiments, the global collectivity of final-state particles can be quantified by anisotropic flow coefficients (𝑣 𝑛 ) . The first-order flow coefficient, also referred to as the directed flow (𝑣 1 ), describes the collective sideward motion of produced particles and nuclear fragments in heavy-ion collisions. It carries information on the very early stage of the collision, especially at large pseudorapidity (𝜂), where it is believed to be generated during the nuclear passage time. Directed flow therefore probes the onset of bulk collective dynamics during thermalization, providing valuable experimental guidance to models of the pre-equilibrium stage. In 2018, the Event Plane Detector (EPD) was installed in STAR and used for the Beam Energy Scan phase-II (BES-II) data taking. The combination of EPD (2.1 < |𝜂| < 5.1) and high-statistics BES-II data enables us to extend the 𝑣 1 measurement to the forward and backward 𝜂 regions. In this paper, we present the measurement of 𝑣 1 over a wide 𝜂 range in Au + Au collisions at $\sqrt{s_{NN}}$ = 19.6 and 27 GeV using the STAR EPD. The results of the analysis at $\sqrt{s_{NN}}$ = 19.6 GeV exhibit excellent consistency with the previous PHOBOS measurement, while elevating the precision of the overall measurement. The increased precision of the measurement also revealed finer structures in heavy-ion collisions, including a potential observation of the first-order event-plane decorrelation. Multiple physics models were compared to the experimental results. Only a transport model and a three-fluid hybrid model can reproduce a sizable 𝑣 1 at large 𝜂 as was observed experimentally. The model comparison also indicates 𝑣 1 at large 𝜂 might be sensitive to the QGP phase transition.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1980

SPS market analysis

A market analysis task included personal interviews by GE personnel and supplemental mail surveys to acquire statistical data and to identify and measure attitudes, reactions and intentions of prospective small solar thermal power systems (SPS) users. Over 500 firms were contacted, including three ownership classes of electric utilities, industrial firms in the top SIC codes for energy consumption, and design engineering firms. A market demand model was developed which utilizes the data base developed by personal interviews and surveys, and projected energy price and consumption data to perform sensitivity analyses and estimate potential markets for SPS.

Goff, H. C.↗
NASA NTRS1993

Imaging the sun in hard x rays using Fourier telescopes

For several years, solar flares have been observed with a variety of instruments confirming that tremendous amounts of energy are locally stored in the solar magnetic field and then rapidly released during the life of the flare. In concert with observations, theorists have attempted to describe the means by which these energetic events occur and evolve. Two competing theories have emerged and have stood the test of time. One theory describes the flare in terms of nonthermal, electron beam injection into a thick target while the other uses a thermal approach. Both theories provide results which are reasonably consistent with current observations; but to date, none have been able to provide conclusive evidence as to the validity of either model. Imaging on short time scales (1 s) and/or small size scales (1 arc s) should give definitive answers to these questions. In order to test whether a realistic telescope can indeed discriminate between models, we construct model sources based upon the thermal and the nonthermal models and calculate the emission as a function of time and energy in the range from 10 to 100 keV. In addition, we construct model telescopes representing both the spatial modulation collimator (SMC) and the rotating modulation collimator (RMC) techniques of observation using random photon counting statistics. With these two types of telescopes we numerically simulate the instrument response to the above two model flares to see if there are distinct x-ray signatures which may be discernable. We find that theoretical descriptions of the primary models of solar flares do indeed predict different hard x-ray signatures for 1 sec time scales and at 1-5 arc sec spatial resolution. However, these distinguishing signatures can best be observed early in the impulsive phase and from a position perpendicular to the plane of the loop. Furthermore, we find that Fourier telescopes with reasonable and currently attainable design characteristics can image these signatures and that the same sensitive areas and short temporal integration times relative to source evolution (i.e., 1 s), the RMC and the SMC will both provide about the same performance.

Campbell, J. W.↗
NASA NTRS2017

Global Energetics of Solar Flares. V. Energy Closure in Flares and Coronal Mass Ejections

In this study we synthesize the results of four previous studies on the global energetics of solar flares and associated coronal mass ejections (CMEs), which include magnetic, thermal, nonthermal, and CME energies in 399 solar M and X-class flare events observed during the first 3.5 years of the Solar Dynamics Observatory (SDO) mission. Our findings are: (1) The sum of the mean nonthermal energy of flare-accelerated particles (E(sub nt)), the energy of direct heating (E(sub dir)), and the energy in coronal mass ejections (E(sub CME)), which are the primary energy dissipation processes in a flare, is found to have a ratio of (E(sub nt)+E(sub dir)+E(sub CME))/E(sub mag) = 0.87±0.18, compared with the dissipated magnetic free energy E(sub mag), which confirms energy closure within the measurement uncertainties and corroborates the magnetic origin of flares and CMEs; (2) The energy partition of the dissipated magnetic free energy is: 0.51±0.17 in nonthermal energy of ≥ 6 keV electrons, 0.17± 0.17 in nonthermal ≥ 1 MeV ions, 0.07 ± 0.14 in CMEs, and 0.07 ± 0.17 in direct heating; (3) The thermal energy is almost always less than the nonthermal energy, which is consistent with the thick-target model; (4) The bolometric luminosity in white-light flares is comparable with the thermal energy in soft X-rays (SXR); (5) Solar Energetic Particle (SEP) events carry a fraction ≈ 0.03 of the CME energy, which is consistent with CME-driven shock acceleration; and (6) The warm-target model predicts a lower limit of the low-energy cutoff at ec ≈ 6 keV, based on the mean differential emission measure (DEM) peak temperature of T(sub e) = 8.6 MK during flares. This work represents the first statistical study that establishes energy closure in solar flare/CME events.

Solar activity↗
NASA NTRS1989

Thermal He(+) in the plasmasphere - Comparison of observations with numerical calculations

Observations made by the retarding ion mass spectrometer on the Dynamics Explorer-1 satellite are used to study the relationship between He(+) and H(+). The observations are compared to theoretical values obtained using the field line interhemispheric plasma model (Richards and Torr, 1988). The observations are presented in the form of statistical L shell distributions and density versus L shell profiles. To obtain agreement between the measured and predicted ion temperature, it must be assumed that approximaterly 55 pct of the energy of the ionospheric photoelectron escape flux is deposited in the plasmasphere.

Newberry, I. T.↗
DOE OSTI2021

Impact of Non-Steady State Operation on Cooling Water Consumption at Coal- and Natural Gas-Fired Power Plants

Increased renewable energy penetration in the electricity grid in coming decades will result in more frequent cycling at thermal power plants. Simultaneously, thermal power plants may face water scarcity with declining availability of cooling water. Therefore, to enhance thermal power plants’ resiliency to water shortages it is important to understand how non-steady conditions due to cycling will impact cooling water consumption and withdrawal intensity. Non-steady operation at power plants has been previously shown to decrease power plant thermal efficiency. Energy balance models have also demonstrated that a decrease in thermal efficiency is expected to increase cooling water consumption intensity. Furthermore, past work has used operating hours data to show idling and cycling gaps where cooling systems operate more than corresponding generators. As a result, an increase in cycling behavior may impact cooling water consumption and withdrawal intensity. This study uses data from the Energy Information Administration (EIA) and Environmental Protection Agency (EPA) to quantify the impact of cycling cooling water consumption intensity for recirculating cooling systems and withdrawal intensity for once-through cooling systems using energy balance and statistical approaches. In a novel application of a fixed effects model to study the effect of temperature on cooling water consumption and withdrawal intensity, this study finds temperature was consistently expected to increase consumption intensity and withdrawal intensity. Non-steady state conditions do not increase cooling water consumption intensity with statistical significance across unit types. However, additional validation of cooling water data is required to confirm these observed trends due to the sensitivity of these findings to model form and concerns with data quality of the dependent variables, cooling water consumption and withdrawal.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

QLBT: a linear Boltzmann transport model for heavy quarks in a quark-gluon plasma of quasi-particles

Abstract We develop a new heavy quark transport model, QLBT, to simulate the dynamical propagation of heavy quarks inside the quark-gluon plasma (QGP) created in relativistic heavy-ion collisions. Our QLBT model is based on the linear Boltzmann transport (LBT) model with the ideal QGP replaced by a collection of quasi-particles to account for the non-perturbative interactions among quarks and gluons of the hot QGP. The thermal masses of quasi-particles are fitted to the equation of state from lattice QCD simulations using the Bayesian statistical analysis method. Combining QLBT with our advanced hybrid fragmentation-coalescence hadronization approach, we calculate the nuclear modification factor $$R_\mathrm {AA}$$ R AA and the elliptic flow $$v_2$$ v 2 of D mesons at the Relativistic Heavy-Ion Collider and the Large Hadron Collider. By comparing our QLBT calculation to the experimental data on the D meson $$R_\mathrm {AA}$$ R AA and $$v_2$$ v 2 , we extract the heavy quark transport parameter $$\hat{q}$$ q ^ and diffusion coefficient $$D_\mathrm {s}$$ D s in the temperature range of $$1-4~T_\mathrm {c}$$ 1 - 4 T c , and compare them with the lattice QCD results and other phenomenological studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Proactive and Reactive Thermal Comfort Behaviors

The expansion of renewable electricity generation, growing demands due to electrification, greater prevalence of working from home, and increasing frequency and severity of extreme weather events, will place new demands on the electric supply and distribution grid. Broader adoption of demand response programs (DRPs) for the residential sector may help meet these challenges; however, experience shows that occupant overrides in DRPs compromises their effectiveness. There is a lack of formal understanding of how discomfort, routines, and other motivations affect DRP overrides and other related human building interactions (HBI). This paper reports preliminary findings from a study of 20 households in Colorado and Massachusetts, US over three months. Participants responded to ecological momentary assessments (EMA) triggered by thermostat interactions and at random times throughout the day. EMAs included Likert-scale questions of thermal preference, preference intensity, and changes to 7 different activity types that could affect thermal comfort, and an opened ended question about motivations of such actions. Twelve tags were developed to categorize motivation responses and analyzed statistically to identify associations between motivations, preferences, and HBI actions. Reactions to changes in the thermal environment were the most frequently observed motivation (118 of 220 responses). On the other hand, almost half (47%) responses were at least partially motivated by non-thermal factors, suggesting limited utility for occupant behavior models founded solely on thermal comfort. Changes in activity level and clothing were less likely to be reported when EMAs were triggered by thermostat interactions, while fan interactions were more likely. Windows, shades, and portable heater interactions had no significant dependence on how the EMA was triggered. These results suggest that better understanding of motivations for HBI may improve effectiveness of demand response programs.

Pathak, Maharshi↗
NASA NTRS2017

Global Energetics of Solar Flares and CMEs: V. Energy Closure

In this study we synthesize the results of four previous studies on the global energetics of solar flares and associated coronal mass ejections (CMEs), which include magnetic, thermal, nonthermal, and CME energies in 399 solar M and X-class flare events observed during the first 3.5 years of the Solar Dynamics Observatory (SDO) mission. Our findings are: (1) The sum of the mean nonthermal energy of flare-accelerated particles (E(sub nt)), the energy of direct heating (E(sub dir)), and the energy in coronal mass ejections (E(sub CME)), which are the primary energy dissipation processes in a flare, is found to have a ratio of (E(sub nt)+E(sub dir)+E(sub CME))/E(sub mag) = 0.87±0.18, compared with the dissipated magnetic free energy E(sub mag), which confirms energy closure within the measurement uncertainties and corroborates the magnetic origin of flares and CMEs; (2) The energy partition of the dissipated magnetic free energy is: 0.51±0.17 in nonthermal energy of ≥ 6 keV electrons, 0.17± 0.17 in nonthermal ≥ 1 MeV ions, 0.07 ± 0.14 in CMEs, and 0.07 ± 0.17 in direct heating; (3) The thermal energy is almost always less than the nonthermal energy, which is consistent with the thick-target model; (4) The bolometric luminosity in white-light flares is comparable with the thermal energy in soft X-rays (SXR); (5) Solar Energetic Particle (SEP) events carry a fraction ≈ 0.03 of the CME energy, which is consistent with CME-driven shock acceleration; and (6) The warm-target model predicts a lower limit of the low-energy cutoff at e(sub c) ≈ 6 keV, based on the mean differential emission measure (DEM) peak temperature of T(sub e) = 8.6 MK during flares. This work represents the first statistical study that establishes energy closure in solar flare/CME events.

Solar activity↗
NASA NTRS2017

Global Energetics of Solar Flares. V. Energy Closure in Flares and Coronal Mass Ejections

In this study we synthesize the results of four previous studies on the global energetics of solar flares and associated coronal mass ejections (CMEs), which include magnetic, thermal, nonthermal, and CME energies in 399 solar M and X-class flare events observed during the first 3.5 years of the Solar Dynamics Observatory (SDO) mission. Our findings are: (1) The sum of the mean nonthermal energy of flare-accelerated particles (E(sub nt)), the energy of direct heating (E(sub dir)), and the energy in coronal mass ejections (E(sub CME)), which are the primary energy dissipation processes in a flare, is found to have a ratio of (E(sub nt) + E(sub dir) + E(sub CME))/E(sub mag) = 0.87±0.18, compared with the dissipated magnetic free energy E(sub mag), which confirms energy closure within the measurement uncertainties and corroborates the magnetic origin of flares and CMEs; (2) The energy partition of the dissipated magnetic free energy is: 0.51±0.17 in nonthermal energy of ≥ 6 keV electrons, 0.17± 0.17 in nonthermal ≥ 1 MeV ions, 0.07 ± 0.14 in CMEs, and 0.07 ± 0.17 in direct heating; (3) The thermal energy is almost always less than the nonthermal energy, which is consistent with the thick-target model; (4) The bolometric luminosity in white-light flares is comparable with the thermal energy in soft X-rays (SXR); (5) Solar Energetic Particle (SEP) events carry a fraction ≈ 0.03 of the CME energy, which is consistent with CME-driven shock acceleration; and (6) The warm-target model predicts a lower limit of the low-energy cutoff at e(sub c) ≈ 6 keV, based on the mean differential emission measure (DEM) peak temperature of T(sub e) = 8.6 MK during flares. This work represents the first statistical study that establishes energy closure in solar flare/CME events.

Solar activity↗
DOE OSTI2021

General relativistic MHD simulations of non-thermal flaring in Sagittarius A*

Sgr A* exhibits regular variability in its multiwavelength emission, including daily X-ray flares and roughly continuous near-infrared (NIR) flickering. The origin of this variability is still ambiguous since both inverse Compton and synchrotron emission are possible radiative mechanisms. The underlying particle distributions are also not well constrained, particularly the non-thermal contribution. In this work, we employ the GPU-accelerated general relativistic magnetohydrodynamics code H-AMR to perform a study of flare flux distributions, including the effect of particle acceleration for the first time in high-resolution 3D simulations of Sgr A*. For the particle acceleration, we use the general relativistic ray-tracing code bhoss to perform the radiative transfer, assuming a hybrid thermal+non-thermal electron energy distribution. We extract ~60 h light curves in the sub-millimetre, NIR and X-ray wavebands, and compare the power spectra and the cumulative flux distributions of the light curves to statistical descriptions for Sgr A* flares. Our results indicate that non-thermal populations of electrons arising from turbulence-driven reconnection in weakly magnetized accretion flows lead to moderate NIR and X-ray flares and reasonably describe the X-ray flux distribution while fulfilling multiwavelength flux constraints. These models exhibit high rms per cent amplitudes, $\gtrsim 150{{\ \rm per\ cent}}$ both in the NIR and the X-rays, with changes in the accretion rate driving the 230 GHz flux variability, in agreement with Sgr A* observations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

AVHRR Surface Temperature and Narrow-Band Albedo Comparison with Ground Measurements for the Greenland Ice Sheet

An ice-surface temperature retrieval algorithm for the Greenland ice sheet was developed using NOAA 11 thermal radiances from channels 4 and 5. Temperature, pressure and humidity profiles, cloud observations and skin temperatures from the Swiss Federal Institute of Technology (ETH) camp, located at the equilibrium line altitude at 49 deg17 min W, 69 deg 34 min N, were used in the LOWTRAN 7 model. Through a statistical analysis of daily clear sky profiles, the coefficients that correct for the atmospheric effects were determined for the ETH-Camp field season (May to August). Surface temperatures retrieved by this method were then compared against the in situ observations with a maximum difference of 0.6 K. The NOAA 11 narrow-band planetary albedo values for channels 1 and 2 were calculated using pre-launch calibration coefficients. Scattering and absorption by the atmosphere were modelled with LOWTRAN 7. Then, narrow-band albedo values for the AVHRR visible and near infrared channels were compared with in situ high resolution spectral reflectance measurements. In the visible band (580-680 nm), AVHRR-derived narrow-band albedo and the in situ measurements corrected with radiative transfer model LOWTRAN 7 showed a difference of less than 2%. For the near infrared channel (725-1100 nm) the difference between the measured and modelled narrow-band albedo was 14%. These discrepancies could be either the result of inaccurate aerosol scattering modelling (lack of the in situ observation), or the result of sensor drift due to degradation.

Haefliger, M.↗
DOE OSTI2022

Preliminary Pilot-scale Study and Techno-economic Analysis of Chemical Heat Pump with Conventional Nuclear Reactors

The energy economy is continually evolving, particularly in terms of primary energy sources, their conversions to useful forms such as electricity and heat, and their utilization in different sectors, in response to socio-political factors. Because nuclear source is clean and non-carbon-emitting energy source, it is crucial to consider its role in the evolution of the energy economy. A pilot-scale study was conducted for Chemical Heat Pump (ChHP) system at three different scales (25-, 100-, and 1000-kW thermal outputs) using steady state thermal model. To establish the viability of selling heat rather than electricity alone, techno-economic analysis was undertaken for advanced Small Modular Reactor (SMR), and SMR paired with varied thermal output ChHP systems was referred to as the nuclear hybrid energy system (NHES) in this study. Using the U.S. Energy Information Administration statistics, pricing for electricity and natural gas were anticipated for U.S. regions (California, Northwest, Midwest, Southwest, New England, and PJM). Based on thermal output from ChHP, advanced SMR with 100 MWth and four alternative NHES scenarios were explored, namely 50-, 10-, 5-, and 1-MWth. Net present value, payback period, discounted cash flow return, and levelized cost of energy were evaluated for all scenarios. Based on the economic analysis, selling heat to high-temperature industrial processes is more profitable compared to selling electricity only. Higher carbon taxes showed significant improvement in economic parameters for NHESs. Providing heat to high-temperature industries could be beneficial, helping to reduce the greenhouse gas emissions by slashing the fossil fuel consumption.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗