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At least 181 records · Page 10

Approximate Dynamic Programming With Enhanced Off-Policy Learning for Coordinating Distributed Energy Resources

Herein this paper proposes an innovative approximate dynamic programming (ADP) method for distributed energy resource coordination with the loss of life of battery energy storage system (BESS) explicitly modeled. The dispatch policy is designed to account for both calendrical and cyclical aging effects on BESS, explicitly modeling the impacts of ambient temperature on BESS lifespan. The proposed ADP employs an adaptive critic method and enhanced off-policy deterministic policy gradient (DPG) strategy, addressing the limitations of the on-policy gradient-based ADP approaches, including inadequate exploration, low data usage, and computational complexity. In particular, a customized policy is proposed to guide the algorithm to explore some promising decisions and thereby improve exploration capability and learning efficiency compared to conventional DPG-based learning approaches, which may struggle to find a global optimum due to random noisy action-based exploration or require expert demonstration with extra effort. The proposed method is illustrated using the IEEE 123-node system and compared with the existing ADP methods to prove solution accuracy and demonstrate the effects of incorporating degradation models into control design. Case studies showed that the proposed ADP effectively coordinates DERs with a 10 times smaller optimization gap compared to existing methods, and the incorporation of the BESS life loss model ensures the expected lifespan and results in significant cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Giant Superelastic Piezoelectricity in Flexible Ferroelectric BaTiO3 Membranes

Mechanical displacement in commonly used piezoelectric materials is typically restricted to linear or biaxial in nature and to a few percent of the material dimensions. Here in this paper, we show that free-standing BaTiO 3 membranes exhibit nonconventional electromechanical coupling. Under an external electric field, these superelastic membranes undergo controllable and reversible “sushi-rolling-like” 180° folding–unfolding cycles. This crease-free folding is mediated by charged ferroelectric domains, leading to giant >3.8 and 4.6 μm displacements for a 30 nm thick membrane at room temperature and 60 °C, respectively. Further increasing the electric field above the coercive value changes the fold curvature, hence augmenting the effective piezoresponse. Finally, it is found that the membranes fold with increasing temperature followed by complete immobility of the membrane above the Curie temperature, allowing us to model the ferroelectric domain origin of the effect.

36 MATERIALS SCIENCE↗

New insights on the nebular emission, ionizing radiation, and low metallicity of Green Peas from advanced modelling

ABSTRACT Low-metallicity, compact starburst galaxies referred to as Green Peas (GPs) provide a unique window to study galactic evolution across cosmic epochs. In this work, we present new deep optical spectra for three GPs from OSIRIS at the 10-m Gran Telescopio Canarias, which are studied using a state-of-the-art methodology. A stellar population synthesis is conducted with 1098 spectral templates. The methodology succeeds at characterizing stellar populations from 0.5 Myr to 10 Gyr. The light distribution shows a large red excess from a single population with ${log}\left({age}\right) \gt 8.5\, \mathrm{yr}$ in the GP sample analysed. This points towards an incomplete characterization of the gas luminosity, whose continuum already accounts between 7.4 and $27.6{{\ \rm per\ cent}}$ in the galaxy sample. The emission spectra are fitted with the largest Bayesian chemical model consisting of an electron temperature, an electron density, the logarithmic extinction coefficient and eleven ionic species under the direct method paradigm. Additionally, building on previous work, we propose a neural networks sampler to constrain the effective temperature and ionization parameter of each source from photoionization model grids. Finally, we combine both methodologies into a 16-dimensional model, which for the first time, simultaneously explores the direct method and photoionization parameter spaces. Both techniques consistently indicate a low-metallicity gas, $7.76\lt 12+{\rm log}\left(O/H \right)\lt 8.04$, ionized by strong radiation fields, in agreement with previous works.

Fernández, V. (ORCID:0000000305315450)↗

Heat Transport Hysteresis Generated Through Frequency Switching of a Time-Dependent Temperature Gradient

A stochastic energetics framework is applied to examine how periodically shifting the frequency of a time-dependent oscillating temperature gradient affects heat transport in a nanoscale molecular model. We specifically examine the effects that frequency switching, i.e., instantaneously changing the oscillation frequency of the temperature gradient, has on the shape of the heat transport hysteresis curves generated by a particle connected to two thermal baths, each with a temperature that is oscillating in time. Analytical expressions are derived for the energy fluxes in/out of the system and the baths, with excellent agreement observed between the analytical expressions and the results from nonequilibrium molecular dynamics simulations. We find that the shape of the heat transport hysteresis curves can be significantly altered by shifting the frequency between fast and slow oscillation regimes. We also observe the emergence of features in the hysteresis curves such as pinched loops and complex multi-loop patterns due to the frequency shifting. The presented results have implications in the design of thermal neuromorphic devices such as thermal memristors and thermal memcapacitors.

36 MATERIALS SCIENCE↗

Correct Interpretations of ENDF-102 Definitions for Resonance Effects

My Uncle Willie circa 1600 wrote “What’s in a name; a rose by any other name would smell as sweet.” I fear in this case we have a somewhat similar problem in that we may be using the same word but are not using the same definition; specifically, the word Unresolved. The simplest physics definition as it applies to neutron resonances, is the energy point where we can no longer see/measure ALL – let me repeat that – ALL - of the individual resonances. That seems simple and clear, but the question is: how to represent resonances beyond this point in order to accurately reproduce the effects we have seen in measurements and expect/need to reproduce in our applications. We know there are more, unseen resonances, otherwise we wouldn’t say Unresolved. The ENDF approach is well defined in ENDF-102 and simple: for ENDF data the only way to represent Unresolved data is by using a theoretical model to define the distribution of resonances, including those that are too narrow to measure (i.e., are unresolved). It is important to note that in ENDF this is the one and only Unresolved model, e.g., there is no provision in ENDF to accurately define individually ALL resonances above the Resolved energy range – by ALL here I mean both those that we can measure and those that we cannot individually measure, but that theory and integral measurements tells us are present. An alternative approach, which would appear to be equally valid, would be to include the latest measured data as tabulated energy expendent data extending upwards in energy above the Resolved energy range. In this approach the evaluation would not include an ENDF style Unresolved energy range; it would only include a Resolved resonance region, followed by tabulated higher energy points, representing the resonances that could be measured beyond the Resolved range. But an important point to note: By listing these resonances above the resolved energy one admits that at least some resonances in this energy range are missing as Unresolved; i.e., they are too narrow or overlapping to measure. The purpose of this paper is to illustrate that the later approach, while done with good intentions, and appearing to be valid/adequate in plots, does not meet the need of our engineering applications. Why? As we will see below, of these two possible approaches, only the ENDF use of a model to statistically include the missing, i.e., unresolved, resonances, can meet our engineering needs to reproduce the integral effects we have measured and understand. Only with this statistical model can we predict and include in our calculated results the important effects of temperature (Doppler broadening), and energy integrals (self-shielding). Below I will first present results using two ENDF/B-VIII.1 evaluations, U235 and U238, that use the correct ENDF-102 definition of an Unresolved resonance region, using a statistical model to include the effects of resonances that theory predicts are present, but are too narrow to measure. These two evaluations reproduce the expected temperature (Doppler) and energy integral (self-shielding) effects that we expect. Next I will present results using one ENDF/B-VIII.1 evaluation, 26-Fe-56, that does not use an ENDF-102 Unresolved resonance region; instead above its Resolved energy range it lists many tabulated energy points, that look like measured data, but by definition, since they are included above the ENDF Resolved energy range there are missing Unresolved resonances, i.e., there are missing the resonances that are too narrow to resolve, i.e., are unresolved. My conclusion, and I hope yours, is that the below figures illustrate that this approach does not reproduce the temperature and energy integrals that we expect and need to accurately calculate results for our fission reactor calculations. As such this approach should not be used in ENDF formatted evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Temperature Effects on Interdiffusion of Al and U-Mo under Irradiation

A high-energy Xe ion irradiation experiment was conducted to investigate the temperature dependence of interdiffusion in bilayer Al-UMo samples under irradiation. The amount of interdiffusion achieved at a fixed dose with the increase of temperature showed a clear transition at 175 degrees C (with an estimated error in the range of ± 10 degrees C) from temperature-independent to temperature-dependent behavior. The activation energy derived from the curve of interdiffusion quantity vs. irradiation temperature is 0.77 ± 0.16 eV. This information has been utilized to understand the temperature effect on the interdiffusion process that occurred at the interfaces of U-Mo particles and the Al matrix in U-Mo/Al dispersion fuels, whose magnitude significantly impacts the fuel's performance. Although this temperature effect was deemed important, it cannot be examined directly using in-pile irradiation data, as fuel temperatures cannot be measured in reactor irradiation and are highly correlated with fission rate and thermal conductivity evolution. To connect the knowledge accumulated from ion irradiation with in-pile irradiation data, simulation of a full-sized U-Mo/Al dispersion fuel plate irradiated in the FUTURE test in the BR2 reactor was performed with the Dispersion Analysis Research Tool (DART), a dispersion fuel performance code. DART is equipped with an interaction or interdiffusion layer (IL) growth correlation formulated to describe the temperature dependence of ion mixing results. The agreement between calculated and measured fuel meat constituent volume fractions and swelling data demonstrated that the temperature effect on in-pile Al-UMo interdiffusion is well captured with the correlation. In this case, the fitted activation energy is 0.70 eV. Considering the uncertainties associated with the ion irradiation data, the activation energy obtained from in-pile data fitting is in accord with that from ion irradiation results.

36 MATERIALS SCIENCE↗

Understanding the Effect of Sample Geometry on Temperature Distribution during Optical Floating Zone Crystal Growth in Vacuum Environment through Heat Transfer Modeling

Optical floating zone furnaces (OFZ) have had a transformative impact on fundamental science due to their ability to rapidly produce large single crystals of a wide variety of complex materials. However, a quantitative understanding of the OFZ growth environment is generally lacking due to the difficulty of measuring the local sample temperatures during OFZ growth, as well as to the general lack of information about the temperature-dependent physical parameters needed to model heat transfer. To overcome these challenges, we apply a physics-based heat transfer model, parametrized by measurements from synchrotron experiments and a machine-learning (ML) algorithm, to simulate the temperature distributions of samples heated in an OFZ furnace in a vacuum environment. This model is used to quantitatively understand how the sample maximum temperature and temperature gradient (key parameters that influence the success of crystal growth) are affected by the rod size, rod shape, and heat-zone position on the rod. The results of this study can be applied to make informed decisions on how crystal growth parameters can be tuned to modify temperature profiles and to optimize crystal growth outcomes even when data on internal sample temperature profiles (e.g., those obtained through in situ synchrotron experiments) are not accessible.

36 MATERIALS SCIENCE↗

Improved Models of R Coronae Borealis Stars

We present an improved numerical method to model subsolar He+CO-WD merger progenitors of R Corona Borealis stars that builds on our previous work. These improvements include a smooth entropy transition from the core to the envelope of the post-merger, inclusion of single-zone nucleosynthesis to mimic the effects of burning during the merger event, and post-processing the models with a larger nuclear network for analysis of s-process nucleosynthesis. We perform a parameter study to understand the effects of the entropy transition, peak temperature, and overshooting on our models. The models that best agree with observations of R Corona Borealis stars are processed with a much larger nuclear network to investigate s-process nucleosynthesis and the dredge-up of s-process products into the outer envelope in detail. We present a model with a significant enhancement in s-process elements, which also agrees with observed surface abundances and isotopic ratios of 16 O/ 16 O and C/O between 1 and 10. Finally, we find that the neutron exposure and initial neutron densities this model requires to obtain such an enhancement are much more consistent with i-process nucleosynthesis.

79 ASTRONOMY AND ASTROPHYSICS↗

Case Study of Integrating High-Temperature Heat Pump with LiBr-H2O Absorption Chiller for Data Center Liquid Cooling

Data centers (DCs) are physical infrastructures that support artificial intelligence workloads. The rapid growth of artificial intelligence is putting substantial pressure on the US power grid. Most of electricity consumed by IT equipment, accounting for 50%-60% of total DC power, ultimately becomes waste heat. This heat is dissipated by DC’s cooling facilities, accounting for an additional 30%-40% of total DC power. Recovering and repurposing this waste heat offers a significant opportunity to enhance energy efficiency and reduce operating costs of DCs. One potential pathway is converting heat to cold using thermal-driven absorption chillers, therefore, reducing the power consumption in DC cooling facilities. Existing studies mainly demonstrate the technical and economic feasibility of repurposing DC’s waste heat for cooling applications but provide limited technical details on how to integrate the thermal-driven absorption chillers with DC cooling systems. In addition, the low-grade waste heat available from DCs must be upgraded to higher temperatures suitable for absorption chillers. This paper presents a case study on integrating high-temperature heat pumps with a LiBr-H2O absorption chiller to use DC waste heat for cooling. A thermodynamic model of single-effect, LiBr-H2O absorption chiller and an empirical model of high-temperature heat pumps were built. The case study considers ASHRAE W17 liquid-cooled DC, with facility service water supplied at 17.0℃ and returned at 25.3℃. The thermal behaviors of absorption chiller components were predicted for the generation temperature ranging from 75.0℃ to 115.0℃. Based on the available waste heat in the integrated system, two waste heat recovery strategies were evaluated: a facility service water-based strategy and cooling water-based strategy. Results indicated that the cooling water-based strategy achieves higher Coefficient of Performance (COPs) than the facility service water-based strategy. The relatively low cooling COPs of single-effect LiBr-H2O absorption chillers could be offset by high heating COP of high temperature heat pumps. The maximum cooling COP of absorption chiller and the overall COP of integrated systems occur at lower generation temperatures, but these conditions also yield lower cooling capacities. In practice, system operation should balance the trade-off between the COP and cooling capacity

Wang, Pengtao [ORNL] (ORCID:0000000214713429)↗

Understanding thermal and mechanical effects on lithium plating in lithium-ion batteries

Lithium plating is one of the main concerns for cell durability, as cyclable lithium and cell capacity are decreased during the process. Thermal and mechanical loads can influence cell behavior, including lithium plating driving forces, as suggested by the Arrhenius equation and the Bruggeman relation, respectively. Hence, a 1D and a 3D model are employed to study the thermal and mechanical effects on lithium plating in a lithium-ion battery with a high areal capacity (4 mAh/cm 2 ). The 1D model assumes uniform mechanical and temperature profile, while the 3D model is capable of capturing the nonuniformity of stress and temperature in the cell. Further, the effects of mechanical deformation and different temperatures on the process of lithium plating are investigated in this study. With the help of the 1D charging simulations, it is observed that lower temperatures increase the risk of lithium plating and the presence of mechanical deformations can accelerate its initiation. Furthermore, 3D charging simulations indicated that folds and boundaries of jellyrolls are more susceptible to lithium plating due to the higher stress concentration and lower temperature, respectively.

25 ENERGY STORAGE↗

Planck 2018 results. V. CMB power spectra and likelihoods

We describe the legacy Planck cosmic microwave background (CMB) likelihoods derived from the 2018 data release. The overall approach is similar in spirit to the one retained for the 2013 and 2015 data release, with a hybrid method using different approximations at low ( ℓ < 30) and high ( ℓ ≥ 30) multipoles, implementing several methodological and data-analysis refinements compared to previous releases. With more realistic simulations, and better correction and modelling of systematic effects, we can now make full use of the CMB polarization observed in the High Frequency Instrument (HFI) channels. The low-multipole EE cross-spectra from the 100 GHz and 143 GHz data give a constraint on the ΛCDM reionization optical-depth parameter τ to better than 15% (in combination with the TT low- ℓ data and the high- ℓ temperature and polarization data), tightening constraints on all parameters with posterior distributions correlated with τ . We also update the weaker constraint on τ from the joint TEB likelihood using the Low Frequency Instrument (LFI) channels, which was used in 2015 as part of our baseline analysis. At higher multipoles, the CMB temperature spectrum and likelihood are very similar to previous releases. A better model of the temperature-to-polarization leakage and corrections for the effective calibrations of the polarization channels (i.e., the polarization efficiencies) allow us to make full use of polarization spectra, improving the ΛCDM constraints on the parameters θ MC , ω c , ω b , and H 0 by more than 30%, and n s by more than 20% compared to TT-only constraints. Extensive tests on the robustness of the modelling of the polarization data demonstrate good consistency, with some residual modelling uncertainties. At high multipoles, we are now limited mainly by the accuracy of the polarization efficiency modelling. Using our various tests, simulations, and comparison between different high-multipole likelihood implementations, we estimate the consistency of the results to be better than the 0.5 σ level on the ΛCDM parameters, as well as classical single-parameter extensions for the joint likelihood (to be compared to the 0.3 σ levels we achieved in 2015 for the temperature data alone on ΛCDM only). Minor curiosities already present in the previous releases remain, such as the differences between the best-fit ΛCDM parameters for the ℓ < 800 and ℓ > 800 ranges of the power spectrum, or the preference for more smoothing of the power-spectrum peaks than predicted in ΛCDM fits. These are shown to be driven by the temperature power spectrum and are not significantly modified by the inclusion of the polarization data. Overall, the legacy Planck CMB likelihoods provide a robust tool for constraining the cosmological model and represent a reference for future CMB observations.

79 ASTRONOMY AND ASTROPHYSICS↗

Physics-Informed Machine Learning Model for Ceramic Matrix Composite Creep

A physics-informed recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear, time-dependent constitutive behavior of ceramic matrix composites (CMCs) driven by matrix damage and constituent creep at the microscale. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the high-fidelity generalized method of cells (HFGMC) approach which calls appropriate creep and damage models for each of the constituents. This coupling permits simulating the nonlinear behavior of CMCs based on constituent response at the microscale along with microstructural features such as fiber and porosity volume fraction and fiber radius. The microscale repeating unit cell is loaded under creep fatigue conditions to replicate the material loading experienced in a turbine engine. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input stress sequence, temperature, and microstructural features, the resulting strain history response while satisfying physical constraints related to creep rate, isochoric inelastic deformation, and strain energy density. The trained surrogate model is shown to effectively match the strain history over quantified distributions of microstructural features and relevant loading regimes and temperatures. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore, the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex microstructures, nonlinear time-dependent material response, and under non-monotonic loading conditions.

ceramic matrix composites↗

Transient fuel performance analysis for the preliminary fuel concept of general atomics fast modular reactor

This study investigates the transient fuel performance of General Atomics Fast Modular Reactor (GA-FMR) during accident scenarios, focusing on the behavior of its innovative fuel system that combines high-assay low enriched uranium dioxide (HALEUO2) fuel with SiGA® ceramic matrix composite silicon carbide cladding. The preliminary fuel design’s response was analyzed during reactivity-initiated accidents (RIA) and loss of coolant accidents (LOCA) using BISON fuel performance analysis code, which included both the diffusion enhanced and BISON-FASTGRASS coupled UO 2 models. The RIA analysis demonstrated that effective reactivity control reduced fuel temperature, though with transient fission gas release resulting in additional tensile stress state on the cladding. LOCA simulations revealed differing predictions between the two models: the BISON UO 2 model showed more transient fission gas release but minimal pellet expansion, while the BISON-FASTGRASS UO 2 model predicted less pronounced fission gas release but more fuel swelling and thermal expansion, potentially leading to pellet-cladding mechanical interaction. Here, these findings highlight critical areas for fuel design optimization and identify knowledge gaps requiring further experimental and computational investigation to advance GA-FMR fuel development.

Lee, Soon K. [Argonne National Laboratory (ANL), A↗

Superior CO 2 /N 2 separation performance of highly branched Poly(1,3 dioxolane) plasticized by polyethylene glycol

With its high content of CO 2 -philic ether oxygen groups, poly(1,3-dioxolane) (PDXLA) has emerged as an attractive platform to achieve excellent CO 2 /N 2 separation properties for post-combustion carbon capture. Herein we demonstrate that the separation properties of PDXLA can be further enhanced by plasticizing with miscible polyethylene glycol (PEG)-based additives using an integrated experimentation and modeling approach. The effects of the chain end groups and loading level of the additives on the physical properties of the blends are thoroughly investigated, including glass transition temperature (T g ), fractional free volume, and gas transport properties, and the effects can be satisfactorily described using models available for homogeneous blends. Notably, a T g -integrated free volume model is adapted to successfully interpret the unified effect of the blend composition and temperature on gas diffusivity and permeability. A sample containing 45 mass% PEG dimethyl ether (PEGDME with a molecular mass of 240 g/mol) displays stable mixed-gas CO 2 permeability of 1540 Barrer and CO 2 /N 2 selectivity of 40 when challenged with a model flue gas at 60 °C, outperforming Robeson's 2008 upper bound. Elucidating how small plasticizers impact gas transport in homogeneous blends may unravel a facile way to design high-performance membranes for gas separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temperature and dose rate effects on dislocation loop formation and decoration in self-ion irradiated high-purity Fe-Cr model alloys

Body-centered cubic (BCC) Fe-based alloys are promising candidate materials for advanced nuclear reactors. A widespread perception is that the addition of Cr favors the formation of ½ <111> dislocation loops. However, the Cr effects on dislocation loop formation/evolution remain unclear due to the limited experimental studies. In this study, we irradiate ultra-high purity bulk BCC Fe-xCr (x = 3, 5, and 8 wt%) with 6.7-8 MeV Fe ions over a wide range of temperatures (Tirr = 250-500 °C) and dose rates (10⁻⁵ to 10⁻³ dpa/s) to two midrange doses (0.35 and 3.5 dpa). The major irradiation-induced microstructures are loop decoration along non-screw dislocation lines at low temperatures and high dose rates as well as self-assembled loops at elevated temperatures. Post-irradiation Burgers vector analysis via g•b method on loops and electron tomography reveals that <001> preponderance is observable in all irradiated Fe-Cr samples at elevated temperature, resulting from stronger elastic energy originating from <001> edge.

Li, Yao [University of Tennessee (UT)]↗

Probing intermediate temperature heat release in autoignition of C3-C4 iso-alcohol/gasoline blends

In this work, we report an experimental and modeling study on the blending effects of C3–C4 iso-alcohols, namely iso-propanol and iso-butanol, on the characteristics of intermediate temperature heat release (ITHR) for a research-grade gasoline (FACE-F) in a rapid compression machine operating at diluted/stoichiometric fuel loading, compressed pressure of 43 bar, and compressed temperatures from 700 to 970 K. Changes in ITHR behavior are characterized through ITHR extent and evolution at 0 to 30 vol% iso-alcohol blending levels. Experimental observations reveal the strong promoting and decelerating effects on ITHR extent and evolution, respectively, within the low-temperature regime for both iso-alcohols, with stronger effects seen for iso-propanol; within the intermediate-temperature regime, the influence of both iso-alcohols diminishes greatly. Comprehensive chemical kinetic modeling is undertaken using a recently developed gasoline surrogate/alcohol model in conjunction with a five-component gasoline surrogate (FGF-LLNL), with good agreement obtained with the experiments for all the blends. Sensitivity, rate of production and flux analyses highlight the importance of chemical kinetic interactions via both fuel-specific and non-fuel-specific reactions. Disabling all the chemical kinetic interactions between iso-alcohol and FGF-LLNL in carbonated/non-fuel-specific species leads to somewhat extended ITHR duration and reduced ignition reactivity. Direct comparison between FGF-LLNL/iso-propanol and FGF-LLNL/iso-butanol blends is also made, where iso-propanol and iso-butanol are found to influence ITHR characteristics via significantly different chemical kinetic interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Best-estimate Modeling of the High Temperature Test Facility with RELAP5-3D

Prismatic HTGRs are a concept of interest for near-term deployment. While plenty of validation data exist for standalone neutronics or multiphysics modeling, the availability of integral effects thermal hydraulics validation data is more limited. The High Temperature Test Facility provides such data and is used as the basis for the High-Temperature Gas-Cooled Reactor Thermal Hydraulics Benchmark. This presentation presents results of best-estimate modeling of HTTF experiments PG-27 and PG-29 using the RELAP5-3D ring model developed at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗