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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.

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At least 37 records · Page 2

A direct contact cooler design for simultaneously recovering latent heat and capturing SO x and NO x from pressurized flue gas

Integrated SO x and NO x removal technology using a direct contact cooler is a promising alternative for cleaning coal combustion flue gas, especially for pressurized combustion systems. Past investigations of integrated SO x and NO x removal have been limited to low-temperature processes, where the flue gas has been cooled upstream of the removal unit, and the moisture in the flue gas has been condensed out. Here this work presents a novel design that recovers the flue gas heat while simultaneously removing SO x and NO x in a single reactive-absorption column – direct contact cooler. A validated model was used to evaluate different direct contact cooler designs. Modeling results suggested that a counter-current column with a single water inlet can scrub 83% of the NO x and 96.5% of the SO x in 115 s, while an optimized design with multiple water inlets enhances the scrubbing of NO x by 9 percentage points and SO x by 3.5 percentage points, due to a 34% increase in residence time. It is also observed that the liquid-phase reaction between absorbed SO x and NO x plays a significant role in the removal of SO 2 from the flue gas for high-temperature scrubbing compared with low-temperature scrubbing. The design reinforces the potential of high-temperature SO x -NO x removal and heat recovery and suggests a means of reducing capital costs for such columns.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the minimum number of radiation field parameters to specify gas cooling and heating functions

Fast and accurate approximations of gas cooling and heating functions are needed for hydrodynamic galaxy simulations. We use machine learning to analyze atomic gas cooling and heating functions in the presence of a generalized incident local radiation field computed by Cloudy. We characterize the radiation field through binned radiation field intensities instead of the photoionization rates used in our previous work. We find a set of 6 energy bins whose intensities exhibit relatively low correlation. We use these bins as features to train machine learning models to predict Cloudy cooling and heating functions at fixed metallicity. We compare the relative SHapley Additive exPlanation (SHAP) value importance of the features. From the SHAP analysis, we identify a feature subset of 3 energy bins (0.5-1, 1-4, and 13-16Ry) with the largest importance and train additional models on this subset. We compare the mean squared errors and distribution of errors on both the entire training data table and a randomly selected 20% test set withheld from model training. The machine learning models trained with 3 and 6 bins, as well as 3 and 4 photoionization rates, have comparable accuracy everywhere, with errors ≳10 times smaller than for the interpolation table of Gnedin and Hollon (2012). We conclude that 3 energy bins (or 3 analogous photoionization rates: molecular hydrogen photodissociation, neutral hydrogen HI, and fully ionized carbon CVI) are sufficient to characterize the dependence of the gas cooling and heating functions on our assumed incident radiation field model.

79 ASTRONOMY AND ASTROPHYSICS↗

On the minimum number of radiation field parameters to specify gas cooling and heating functions

Fast and accurate approximations of gas cooling and heating functions are needed for hydrodynamic galaxy simulations. We use machine learning to analyze atomic gas cooling and heating functions computed by Cloudy in the presence of a generalized incident local radiation field. We characterize the radiation field through binned radiation field intensities instead of the photoionization rates used in our previous work. We find a set of 6 energy bins whose intensities exhibit relatively low correlation. We use these bins as features to train machine learning models to predict Cloudy cooling and heating functions at fixed metallicity. We compare the relative SHapley Additive exPlanation (SHAP) value importance of the features. From the SHAP analysis, we identify a feature subset of 3 energy bins ($0.5-1, 1-4$, and $13-16 \, \mathrm{Ry}$) with the largest importance and train additional models on this subset. We compare the mean squared errors and distribution of errors on both the entire training data table and a randomly selected 20% test set withheld from model training. The machine learning models trained with 3 and 6 bins, as well as 3 and 4 photoionization rates, have comparable accuracy everywhere, with errors $\gtrsim 10$ times smaller than for the interpolation table of Gnedin and Hollon (2012). We conclude that 3 energy bins (or 3 analogous photoionization rates: molecular hydrogen photodissociation, neutral hydrogen HI, and fully ionized carbon CVI) are sufficient to characterize the dependence of the gas cooling and heating functions on our assumed incident radiation field model.

79 ASTRONOMY AND ASTROPHYSICS↗

SEASONAL PERFORMANCE SIMULATION OF A GAS-FIRED CHEMISORPTION HEAT PUMP FOR RESIDENTIAL HEATING IN COLD CLIMATE

The gas-fired chemisorption heat pump (CSHP) is a promising technology for high-efficiency cold-climate residential heating. The CSHP utilizes the heat of reversible chemical reactions between sorbent and refrigerant to extract heat from cold ambient and supply high-temperature heat to the indoors. The efficiency of CSHP depends on the ambient and heat rejection temperatures. This study evaluates the seasonal performance of a CSHP by first develop a dynamic system model to generate a performance map for various ambient and heat-supply temperatures; then the bin method is used to evaluate the CSHP seasonal performance in two cold-climate locations for space and water heating.

Yang, Zhiyao↗

Benchmarking the design of the cryogenics system for the underground argon in DarkSide-20k

DarkSide-20k (DS-20k) is a dark matter detection experimentunder construction at the Laboratori Nazionali del Gran Sasso (LNGS)in Italy. It utilises ∼ 100 t of low radioactivity argon from anunderground source (UAr) in its inner detector, with half serving astarget in a dual-phase time projection chamber (TPC). The UArcryogenics system must maintain stable thermodynamic conditionsthroughout the experiment's lifetime of over10 years. Continuous removal ofimpurities and radon from the UAr is essential for maximising signalyield and mitigating background. We are developing an efficient andpowerful cryogenics system with a gas purification loop with atarget circulation rate of1000 slpm. Central to itsdesign is a condenser operated with liquid nitrogen which is pairedwith a gas heat exchanger cascade, delivering a combined coolingpower of more than 8 kW. Here wepresent the design choices in view of the DS-20k requirements, inparticular the condenser's working principle and the coolingcontrol, and we show test results obtained with a dedicatedbenchmarking platform at CERN and LNGS. We find that the thermalefficiency of the recirculation loop, defined in terms of nitrogenconsumption per argon flow rate, is95 % and the pressure in the testcryostat can be maintained within±(0.1–0.2) mbar. Wefurther detail a 5-day cool-down procedure of the test cryostat,maintaining a cooling rate typically within-2 K/h, as required for theDS-20k inner detector. Additionally, we assess the circuit's flowresistance, and the heat transfer capabilities of two heat exchangergeometries for argon phase change, used to provide gas forrecirculation. We conclude by discussing how our findings influencethe finalisation of the system design, including necessarymodifications to meet requirements and ongoing testing activities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Bio-inspired alula-based winglet design for enhanced heat transfer in high temperature fin-and-tube heat exchangers

Fin-and-tube heat exchangers (FTHEs) are widely used for high-temperature flue-gas heat recovery, but their performance is often limited by wake regions and non-uniform fin-surface temperatures. This study proposes and numerically evaluates four bio-inspired longitudinal vortex generator (VG) configurations in a high-temperature FTHE with flue-gas inlet temperature ∼1230 K: double-delta, curved double-delta, alula, and a new curved-alula geometry. The reference fin is not hydraulically plain; it already incorporates leading-edge separation columns and convex protrusions, so the alula-type winglets are assessed as downstream add-ons acting on a strongly disturbed flow. In a second step, perforations (one, two and three circular holes) are introduced into the curved-alula VGs to further tailor the flow field. Three-dimensional simulations with the Shear Stress Transpor (SST) $k - ω$ model, temperature-dependent flue-gas properties and conjugate conduction are carried out for gas-side Reynolds numbers $Re_g ≈ 8.0$ x $10^2 - 3.6$ x $10^3$ (mass flow rates 0.5 – 2.5 g/s), and the designs are compared in terms of surface heat flux, Nusselt number, friction factor and hydrothermal performance factor (HTPF). For this already-promoted fin, the additional downstream winglets provide moderate, incremental hydrothermal gains. At the highest Reynolds number, the best non-perforated design (curved-alula) increases surface heat flux from 1630.9 to 1794.7 kW/m² (∼ 10 % gain) and the Nusselt number from 227.6 to 242.6 (∼ 7 % gain), while the friction factor rises from 0.26 to about 0.30, yielding HTPF values close to unity (∼ 0.9 – 1.0). Introducing circular perforations into the curved-alula winglets acts mainly as a wake-bleeding refinement: the three-hole configuration provides a heat flux of 1824.7 kW/m² and a pressure drop of 127.9 Pa, with HTPF in the range ∼ 1.03 – 1.14 and a small (∼ 1 – 3 %) improvement over the solid curved-alula design. Flow-field analysis shows that the perforated curved-alula VGs shrink tube-wake regions, thin the thermal boundary layer and homogenize the fin-surface temperature (outlet-gas temperature ∼ 510 – 520 K and fin-surface temperature ∼ 420 – 421 K for the three-hole case). An optimal flue-gas mass flow rate of ∼ 1 g/s ($Re_g ≈ 1.5$ x $10^3$) is identified, beyond which additional heat-transfer gains are offset by rapidly increasing pressure losses. Overall, the results highlight that initial fin geometry and VG placement are as important as VG shape: alula-based winglets are expected to yield larger relative gains on simpler flat-fin layouts or when positioned closer to the fin leading edge and tube

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Toward extreme high-temperature supercritical CO 2 power cycles: Leakage characterization of ceramic 3D-printed heat exchangers

We report future supercritical carbon dioxide (sCO 2 ) Brayton power cycles demand high-performance gas-to-gas heat exchangers (HXs) operating under extreme temperature and pressure conditions at which most existing superalloy materials fail to function safely. Ceramic HXs are deemed excellent candidates for advanced sCO 2 power plants as they can withstand high-temperature working environments. Particularly, ceramic 3D printing enables compact HX topologies employing complex and efficient heat transfer features. However, ceramic 3D-printed walls separating hot and cold flow streams are susceptible to a through-plane leakage inherent to a powder-based manufacturing process, including ceramic 3D printing. A potential leakage through ceramic separating walls poses a significant challenge in developing reliable ceramic 3D-printed HXs and could deteriorate thermal performance. In this study, various parameters, including feedstock slurry, 3D-printing direction, and post-processing conditions, are considered, for the first time, to characterize the argon gas leakage rate associated with alumina 3D-printed parts. Three 3D-printed ceramic structures of flat plates, curved tubes, and small-scale plate-and-frame HXs with various thicknesses are systematically studied to determine powder and ceramic 3D-printing conditions to eliminate the through-plane leakage. The results showed that an alumina 3D-printed plate with a thickness of 0.75 mm demonstrates a permeability of 6 x 10 -4 milli-darcy. An alumina 3D-printed tube with a wall thickness of 0.9 mm revealed a permeability of 9.6 x 10 -7 milli-darcy. Furthermore, leakage test results of functional 3D-printed modules showed a dependency on the 3D-printing direction. Particularly, alumina cell-scale HXs employing 1.5-mm-thick horizontal and vertical 3D-printed separating walls demonstrated impermeability and gas permeability of 7.2 x 10 -5 millidarcy, respectively. Insights gained from the present study facilitate the development of complex ceramic 3D-printed HXs and other balance of plant components for next-generation high-temperature high-pressure sCO 2 power cycles.

36 MATERIALS SCIENCE↗

Investigation of the Mechanisms Underpinning Plasma-Catalyst Interaction for the Conversion of Methane to Oxygenates

Plasma catalysis is a promising approach to further enhance the conversion of methane into value-added products such as methanol. In this work, the mechanisms enabling the conversion of methane to CO, CO 2 and methanol enabled by plasma-enhanced catalysis were investigated. A catalyst reactor was incorporated downstream of the plasma jet to enable the separation between plasma generation and the catalyst bed. An enhancement in CH 3 OH and CO 2 production was observed for the shortest distance between the plasma and catalyst compared to the plasma-only case. Plasma-enabled gas heating was shown not to be responsible for the observed synergy while a gas temperature increase as low as 30-40 K significantly impacted desorption rates of CH 3 OH/C 2 H 5 OH on alumina particles. Correlations between molecular beam mass spectrometry (MBMS) measurements at the inlet and outlet of the catalytic reactor suggest that the observed synergistic effect was caused by radical species most likely the CH 3 O 2 radical. As a result, this study shows that surface reactions induced by radicals such as alkylperoxy radicals might play an important role in surface reactions in plasma-catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Cost-Optimized Cold Climate Heat Pump Development and Field Test

Cold climate heat pumps (CCHPs) expand the heat pump market to climates where heating demand is dominant. They can achieve more than 70% energy savings compared with electric resistance heating and operate at lower cost than using tank-stored propane to fuel a furnace. A high-efficiency heat pump with a heating seasonal performance factor (HSPF)—as defined by the Air-Conditioning, Heating, and Refrigeration Institute (AHRI 2008)—greater than 10.0 would be more efficient than gas heating in terms of source energy. However, developing a cost-effective CCHP involves some challenges. A typical single-speed, air-source heat pump (ASHP) with an HSPF of 7.7 Btu/Wh does not work well under cold outdoor temperature conditions typical of cold climate locations for four major reasons: 1. Discharge temperature is too high—The low suction pressure and high compression pressure ratio at low ambient temperatures causes high compressor discharge temperatures in excess of the maximum limit for many of the compressors on the market. Furthermore, system charge of a heat pump is usually optimized in the cooling mode, which leads to overcharge conditions in the heating mode, further increasing the discharge temperature. 2. Heating capacity is insufficient if sized to meet the building design cooling load— Heating capacity of a single-speed heat pump decreases with ambient temperature. The heating capacity at -13°F (-25°C) typically decreases to 20%–40% of the rated heating capacity at 47°F (8.3°C) (~equivalent to the rated cooling capacity at 95°F [35°C]). Therefore, a single-speed heat pump, typically sized to match the building design cooling load, cannot provide adequate heating capacity to match the building heating load at low ambient temperatures. The capacity deficit is filled by inefficient resistance heat, thus lowering the system efficiency and significantly increasing power demand. 3. Cyclic loss is significant if sized to meet the building design heating load—If a single-speed heat pump is sized to meet the heating load, it will be significantly oversized relative to the cooling load in many cold climates. This will cause excessive on/off cyclic loss during the cooling and heating operations at moderately low ambient temperatures. Thus, capacity modulation capability (e.g., using a variable-speed or multi-stage compressor) is necessary for a CCHP, which uses its full capacity to meet the peak heating load and partial capacity to meet the cooling and part-load heating loads. 4. Coefficient of performance (COP) is low—Heating COP degrades significantly at low ambient temperatures owing to the large temperature difference between the heat source and sink. A target CCHP should be sized to meet the building design heating load while minimizing the cyclic loss for the cooling and heating operations at moderate ambient temperatures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development and Test Progress Towards a Supercritical Carbon Dioxide-Based Gas Turbine Waste Heat Recovery System

Supercritical carbon dioxide systems are the focus of significant recent research efforts and promise compact, high-efficiency architecture for gas turbine waste heat recovery for pipeline gas turbines. The waste heat recovery system improves operating efficiency by converting waste heat to additional electric power, which increases overall system efficiency by 35% at the design point, and also significantly improves part-load performance. This paper describes the system design and component selection for a 5.7 MWe waste heat recovery system based on an integrally-geared compressor-expander architecture, including the thermodynamic cycle development, system architecture and component trade studies, and final selection. Validation test results for critical first-of-a-kind compressor and turbine component technologies are also presented, demonstrating full-pressure performance and progress towards commercialization.

wilkes, Jason↗

Photochemically induced acousto-optics in gases

Acousto-optics consists of launching acoustic waves in a medium (usually a crystal) in order to modulate its refractive index and create a tunable optical grating. Here, in this article, we present the theoretical basis of an alternative scheme to generate acousto-optics in a gas, where the acoustic waves are initiated by the localized absorption (and thus gas heating) of spatially modulated UV light, as was demonstrated by Michine and Yoneda [Commun. Phys. 3, 24 (2020)]. We identify the chemical reactions initiated by the absorption of UV light via the photodissociation of ozone molecules present in the gas, and calculate the resulting temperature increase in the gas as a function of space and time. Solving the Euler fluid equations shows that the modulated, isochoric heating initiates a mixed acoustic-entropy wave in the gas, whose high-amplitude density (and thus refractive index) modulation can be used to manipulate a high-power laser. We calculate that diffraction efficiencies near 100% can be obtained using only a few millimeters of gas containing a few percent ozone fraction at room temperature, with UV fluences of less than 100 mJ/cm 2 —consistent with the experimental measurements. Our analysis suggests possible ways to optimize the diffraction efficiency by changing the buffer gas composition. Gases have optics damage thresholds 2–3 orders of magnitude beyond those of solids; these optical elements should therefore be able to manipulate kilojoule-class lasers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Materials Challenges and Opportunities for Energy Generation, Conversion, Delivery, and Storage (Applied Energy Tri-Laboratory Consortium Workshop Report)

This report documents the outcomes of the Tri-Laboratory Materials Workshop that was held July 31 and August 1, 2019 to begin addressing the needs, opportunities, and challenges associated with the development, fabrication, and testing of the needed materials and components for integrated hybrid energy systems (i.e., incorporating nuclear, fossil, and renewables for electric and thermal applications). This was accomplished by assembling the research program leads and principal investigators at Idaho National Laboratory (INL), National Energy Technology Laboratory (NETL), and National Renewable Energy Laboratory (NREL), who support the research and development of new technology and system integration. The team then identified and prioritized key materials development needs. This effort was intended to enhance communications and synergy among the Tri-Lab partners. Advanced functional and structural materials are central to transformative energy technologies for energy generation, conversion, delivery, and storage. With that in mind, the workshop focused on identifying and assessing the foundational materials research needs at both the basic and applied levels. Materials challenges include the ability to withstand harsh environments, such as high temperatures and pressures, corrosion, oxidation, or irradiation while maintaining flexible mission profiles and long service lifespans. Advanced energy system material challenges and needs range from materials for the capture, upgrading/concentration, storage, and delivery of low-grade heat to materials for high temperature environments that involve liquid metals, molten salt, and very high temperature gas heat delivery and storage systems. Material improvements are needed for hybrid energy systems due to accelerated corrosion and stress-fatigue failure of materials and equipment, which results from increased frequency and amplitude of thermal, mechanical, and electrical cycling of systems components. Multifunctional materials are needed for high temperature solid-oxide fuel cells, advanced electrochemical reactors, and in-process separation. Relative to materials manufacturing, application of advanced additive and subtractive methods need to be understood to develop both thin-layer homogenous materials and materials of graded composition. Materials modeling and machine learning will be critical to accelerate the design and production of power electronics, and nuclear reactor materials and fuel, as well as to gain an understanding of beneficial materials phenomena or deleterious microstructure evolution. There is also a need for standardized models, computational structures, data reporting protocols and modeling tools across the three laboratories. This would allow consistent results, analysis, and data sharing. Combining computational capabilities between the three laboratories (e.g., hardware, software) would greatly increase computational capabilities and throughput. The workshop identified the need for laboratories to anticipate and address problems that will occur during scale-up. Laboratory work must connect with industry to ensure that research focuses on processes that are scalable and marketable. Industry input and perspective are essential to guide laboratory research to meet these requirements and deploy new technology in industrial demonstrations. Another aspect of scale-up is the integration of multiple systems since new challenges often arise at the subsystem interfaces. Establishing a scale-up manufacturing demonstration/pilot plant, potentially as an industrial user facility, would be beneficial to the laboratories and industry. That modular scale-up manufacturing demonstration/pilot plant would allow researchers to find and resolve interface problems that cannot be identified by focusing only on individual parts. Communication exchanges among the organizers, attendees, and workshop survey responses indicate that the workshop was successful in achieving its goal to identify key technology gaps and research needs. Strong positive feedback was received on the sharing of ideas, capabilities, talent, and passion to move forward on the materials-related action items.

36 MATERIALS SCIENCE↗

Fluid-kinetic modeling of a high power density radio frequency inductively coupled positive hydrogen ion source

High power density radio-frequency (RF) inductively coupled positive ion sources are attractive candidates for next-generation neutral beam injection (NBI) systems, where higher injected power and longer pulse lengths are desired without sacrificing source reliability. Operating at absorbed power densities of order $\gt 1~\mathrm{W\,cm}^{-3}$ places these sources in a regime with stronger gas heating, higher dissociation, and non-Maxwellian electron energy distributions. The Large Uniform Plasma for Ionizing Neutrals (LUPIN) is an RF inductively coupled plasma source designed to explore this high power density regime and to provide guidance for a positive ion source upgrade for the DIII-D NBI system. LUPIN is designed to operate at up to 20 kW of RF power at 2 MHz, coupling energy through a cylindrical quartz vessel to achieve target ion current densities of $2100\,\mathrm{A\,m}^{-2}$ . This paper presents fluid-kinetic modeling of LUPIN using the hybrid plasma equipment model where electrons are treated kinetically, and the simulations reveal that electron energy distribution function transitions from nearly Maxwellian in the core to bi-Maxwellian towards the edge. Parametric simulations investigate the effects of RF power, gas pressure, and frequency on plasma density, ion flux, and uniformity. Parametric sweeps reveal that increasing power shifts the primary ionization channel from molecular to atomic with diminishing flux gains due to skin-depth contraction and gas rarefaction. Higher frequency localizes heating and increases $\mathrm{H}_2^+$ and $\mathrm{H}_3^+$ delivery to the grid, while elevated pressure boosts ionization yet hinders ion transport due to increase in collisionality.

inductively coupled plasma↗

Kinematic and thermal signatures of the directly imaged protoplanet candidate around Elias 2−24

We report kinematic and thermal signatures associated with the directly imaged protoplanet candidate in the Elias 2–24 disc. Using the DSHARP (Disc Substructures at High Angular Resolution Project) ALMA (Atacama Large Millimetre/submillimetre Array) observations of the 12 CO J = 2 − 1 line, we show that the disc kinematics are perturbed, with a detached CO emission spot at the location of the planet candidate and traces of spiral wakes, and also that the observed CO emission intensities require local heating. While the foreground extinction hides the velocity channels associated with the planet, preventing a planet mass estimate, the level of gas heating implied by the CO emission indicates the presence of a warm, embedded giant planet. Comparison with models shows that this could either be a ≳5 M Jup or a lower mass (≳2 M Jup ) but accreting protoplanet.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploring the dependence of gas cooling and heating functions on the incident radiation field with machine learning

ABSTRACT Gas cooling and heating functions play a crucial role in galaxy formation. But, it is computationally expensive to exactly compute these functions in the presence of an incident radiation field. These computations can be greatly sped up by using interpolation tables of pre-computed values, at the expense of making significant and sometimes even unjustified approximations. Here, we explore the capacity of machine learning to approximate cooling and heating functions with a generalized radiation field. Specifically, we use the machine learning algorithm XGBoost to predict cooling and heating functions calculated with the photoionization code cloudy at fixed metallicity, using different combinations of photoionization rates as features. We perform a constrained quadratic fit in metallicity to enable a fair comparison with traditional interpolation methods at arbitrary metallicity. We consider the relative importance of various photoionization rates through both a principal component analysis (PCA) and calculation of SHapley Additive exPlanation (shap) values for our XGBoost models. We use feature importance information to select different subsets of rates to use in model training. Our XGBoost models outperform a traditional interpolation approach at each fixed metallicity, regardless of feature selection. At arbitrary metallicity, we are able to reduce the frequency of the largest cooling and heating function errors compared to an interpolation table. We find that the primary bottleneck to increasing accuracy lies in accurately capturing the metallicity dependence. This study demonstrates the potential of machine learning methods such as XGBoost to capture the non-linear behaviour of cooling and heating functions.

79 ASTRONOMY AND ASTROPHYSICS↗

Seeking Self-regulating Simulations of Idealized Milky Way–like Galaxies

Abstract Precipitation is potentially a mechanism through which the circumgalactic medium (CGM) can regulate a galaxy’s star formation. Here, we present idealized simulations of isolated Milky Way–like galaxies intended to examine the ability of galaxies to self-regulate their star formation, in particular via precipitation. We also examine the impact of rotation in the CGM. Using six simulations, we explore variations in the initial CGM t cool / t ff ratio and rotation profile. Those variations affect the amount of gas accretion and star formation within the galactic disk. To encourage this accretion and better study its dependence on CGM structure, we gradually increase the efficiency of stellar feedback during the first half of our simulations. Yet despite this gradual increase, the resulting outflows quickly evacuate large, hot cavities within the CGM and even beyond r 200 . Some of the CGM gas avoids interacting with the cavities and is able to feed the disk along its midplane, but the cooling of feedback-heated gas far from the midplane is too slow to supply the disk with additional gas. Our simulations illustrate the importance of physical mechanisms in the outer CGM and IGM for star formation regulation in Milky Way–scale halos.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeled Results of Four Residential Energy Efficiency Measure Packages for Deriving Advanced Building Construction Research Targets

The Advanced Building Construction (ABC) Initiative from the U.S. Department of Energy Building Technologies Office is working to accelerate industrialized construction innovations for decarbonizing buildings. To inform performance and cost targets for research under the ABC Initiative, this analysis used the ResStock™ tool to evaluate the energy savings, utility bill impacts, and carbon emissions impacts of four simulated upgrade packages with specific target performance levels on a large sample of residential dwelling units (approximately 550,000) representative of the U.S. housing stock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗