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DOE OSTI2021

Evaluating the benefits of kinetic Monte Carlo and microkinetic modeling for catalyst design studies in the presence of lateral interactions

Popular computational catalyst design strategies rely on the identification of reactivity descriptors, which can be used along with Brønsted–Evans–Polanyi (BEP) and scaling relations as input to a microkinetic model (MKM) to make predictions for activity or selectivity trends. The main benefit of this approach is related to the inherent dimensionality reduction of the large material space to just a few catalyst descriptors. Conversely, it is well documented that a small set of descriptors is insufficient to capture the intricacies and complexities of a real catalytic system. The inclusion of coverage effects through lateral adsorbate-adsorbate interactions can narrow the gap between simplified descriptor predictions and real systems, but mean-field MKMs cannot properly account for local coverage effects. This shortcoming of the mean-field approximation can be rectified by switching to a lattice-based kinetic Monte Carlo (kMC) method using cluster expansion representation of adsorbate–adsorbate lateral interactions. Using the prototypical CO oxidation reaction as an example, we critically evaluate the benefits of kMC over MKM in terms of trend predictions and computational cost when using only a small set of input parameters. After confirming that in the absence of lateral interactions the kMC and MKM approaches yield identical trends and mechanistic information, we observed substantial differences between the two kinetic models when lateral interactions were introduced. Here, the mean-field implementation applies coverage corrections directly to the descriptors, causing an artificial overprediction of the activity of strongly binding metals. In contrast, the cluster expansion in kMC implementation can differentiate among the highly active metals but it is very sensitive to the set of included interaction parameters. Considering that computational screening relies on a minimal set of descriptors, for which MKM makes reasonable trend predictions at a ca. three orders of magnitude lower computational cost than kMC, the MKM approach does provide a better entry point for computational catalyst design.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Evaluation of UAV-derived multimodal remote sensing data for biomass prediction and drought tolerance assessment in bioenergy sorghum

Screening for drought tolerance is critical to ensure high biomass production of bioenergy sorghum in arid or semi-arid environments. The bottleneck in drought tolerance selection is the challenge of accurately predicting biomass for a large number of genotypes. Although biomass prediction by low-altitude remote sensing has been widely investigated on various crops, the performance of the predictions are not consistent, especially when applied in a breeding context with hundreds of genotypes. In some cases, biomass prediction of a large group of genotypes benefited from multimodal remote sensing data; while in other cases, the benefits were not obvious. In this study, we evaluated the performance of single and multimodal data (thermal, RGB, and multispectral) derived from an unmanned aerial vehicle (UAV) for biomass prediction for drought tolerance assessments within a context of bioenergy sorghum breeding. The biomass of 360 sorghum genotypes grown under well-watered and water-stressed regimes was predicted with a series of UAV-derived canopy features, including canopy structure, spectral reflectance, and thermal radiation features. Biomass predictions using canopy features derived from the multimodal data showed comparable performance with the best results obtained with the single modal data with coefficients of determination (R 2 ) ranging from 0.40 to 0.53 under water-stressed environment and 0.11 to 0.35 under well-watered environment. The significance in biomass prediction was highest with multispectral followed by RGB and lowest with the thermal sensor. Finally, two well-recognized yield-based drought tolerance indices were calculated from ground truth biomass data and UAV predicted biomass, respectively. Results showed that the geometric mean productivity index outperformed the yield stability index in terms of the potential for reliable predictions by the remotely sensed data. Collectively, this study demonstrated a promising strategy for the use of different UAV-based imaging sensors to quantify yield-based drought tolerance.

09 BIOMASS FUELS↗

DOE OSTI2023

Evaluation of dual-weighted residual and machine learning error estimation for projection-based reduced-order models of steady partial differential equations

Projection-based reduced-order models (pROMs) show great promise as a means to accelerate many-query applications such as forward error propagation, solving inverse problems, and design optimization. In order to deploy pROMs in the context of high-consequence decision making, accurate error estimates are required to determine the region(s) of applicability in the parameter space. The following paper considers the dual-weighted residual (DWR) error estimate for pROMs and compares it to another promising pROM error estimate, machine learned error models (MLEM). Here, we show how DWR can be applied to ROMs and then evaluate DWR on two partial differential equations (PDEs): a two-dimensional linear convection–reaction–diffusion equation, and a three-dimensional static hyper-elastic beam. It is shown that DWR is able to estimate errors for pROMs extrapolating outside of their training set while MLEM is best suited for pROMs used to interpolate within the pROM training set.

42 ENGINEERING↗

DOE OSTI2026

Evaluation of coal-associated sediments, wastes, and AMD sludge in the Southern Appalachian Basin as feedstock materials for REE and Li recovery

Critical minerals (CM) such as rare earth elements (REE+) and Lithium (Li) are essential to technological innovation, energy transitions, global economic and defense security, necessitating the search for unconventional resources and efficient recovery methods to avert supply chain disruptions. Here, this study evaluates coal-associated sediments (underclay and roof rock) and wastes from the Pennsylvanian Pottsville Formation of the Southern Appalachian Basin (SAB) as potential feedstocks for CM recovery. A total of 34 samples (15 underclays, 12 roof rocks, 5 Acid Mine Drainage (AMD) sludges, and 2 coal mining wastes) were characterized using XRD, XRF, ICP-MS, and μ-XRF analytical methods. The REE+ and Li concentrations of these materials ranged from 46.8 to 334.4 ppm and from 11.1 to 519 ppm, respectively, with one underclay sample (Hendrix 3456) yielding the highest values for both. Bulk mineralogy for all samples was dominated by aluminosilicate clay phases, particularly illite and kaolinite. All samples exhibited REY def, rel% values >26% and C outl indices that ranged from 0.69 to 0.94, classifying their REE ore potential as Category II (Promising) as defined by Seredin and Dai (2012). Extractability tests (EPA method 3051 A) yielded low REE+ and Li recoveries, with maximum values of 3.3% and 3.6%, respectively, suggesting associations with resistant minerals like clay and phosphates. Elemental mapping indicates that REE+ is associated with phosphate, whereas statistical analysis suggests that REE+ are associated with aluminosilicates, suggesting heterogeneous associations or minimal phosphate contribution. Li also correlated positively with Al 2 O 3 , indicating an aluminosilicate host. This study highlights the potential of coal-associated sediments in the SAB.

Clay minerals↗

DOE OSTI2020

Evaluation of semi-empirical soot models for nonpremixed flames with increased stoichiometric mixture fraction and strain

Due to the size and complexity of industrial-scale systems and computing limitations, semi-empirical soot models are often employed in CFD simulations rather than computationally-expensive detailed models. Many of these models were developed for specific applications with unique characteristic timescales and/or validated only under fuel-air combustion conditions. Hence, their use in different contexts, such as oxy-combustion, could lead to inaccurate predictions. In this study, twelve semi-empirical models (1-step or 2-step) are evaluated on their ability to respond to changes in stoichiometric mixture fraction (Z st ) and strain in a series of ethylene counterflow flames which span the experimental sooting-to-non-sooting (yellow to blue) transition. A unique approach of plotting soot formation rate in normalized, local equivalence ratio space is introduced to aid in the analysis. Results show that no existing model is able to predict a blue flame when Z st is increased beyond the experimentally-measured sooting limit. Many models give the counter-intuitive result of increasing peak and/or integrated soot volume fraction (svf) as Z st increased, contrary to experimental observations. Two models are able to successfully predict a blue flame upon increase of strain to the sooting limit value. For two-step models, the strong dependence of growth rate on surface area results in high sensitivity of svf to changing flame boundary conditions, but with mixed accuracy. There is still a significant need for a robust semi-empirical model which can accurately predict soot fraction in systems with oxygen-enrichment or variable strain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Re-evaluation of rate constants for the reaction N 2 H 4 (+ M) $^→_←$ NH 2 + NH 2 (+ M)

Rate constants for the dissociation/recombination reaction N 2 H 4 (+ M) $^→_←$ NH 2 + NH 2 (+ M) are determined by a combination of quantum-chemical calculations and statistical unimolecular rate theory. Between 1100 and 2500 K, limiting low-pressure rate constants for hydrazine dissociation in the bath gas Ar of k 0 = [Ar] 6.1 × 10 20 (T/1000 K) –7.3 exp (-34490 K/T) cm 3 mol –1 s –1 , limiting high-pressure rate constants of k ∞ = 7.6 × 10 16 (T/1000 K) –1.0 exp(-33600 K/T) s –1 , and center broadening factors of the falloff curves (between 1100 and 1600 K in Ar) of F cent = 0.71 exp(- T/1460 K) + 0.29 exp(- T/21 K) + exp(-13400 K/T) were calculated. Using equilibrium constants K C = 1.7 × 10 3 (T/1000 K) –1.5 exp(-33,460 K/T) mol cm –3 , between 300 and 600 K limiting low-pressure rate constants for the reverse recombination of NH 2 radicals in the bath gas N 2 of k rec,0 = [N 2 ] 4.4 × 10 20 (T/400 K) –6.9 exp (-1630 K/T) cm 6 mol –2 s –1 , limiting high-pressure rate constants of k rec,∞ = 4.4 × 10 13 (T/1000 K) 0.44 exp(-140 K/T) cm 3 mol -1 s –1 , and center broadening factors (between 300 and 600 K in N 2 ) of F cent = exp(- T/1130 K) + exp (-10340 K/T) were obtained. A comparison with experimental results for hydrazine dissociation from the literature suggests incomplete falloff extrapolations toward k ∞ and experimental problems in the determination of k 0 at temperatures above about 1600 K. Finally, implications of the present re-evaluated rate constants for the modeling of high temperature ammonia oxidation kinetics are discussed, showing an only small influence of their precise values on the overall properties of the process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

The compositional optimization and secondary phases evaluation regarding the creep resistance in Grade 91 steel through the CALPHAD approach

The critical secondary phases along with critical temperatures in regard to the creep resistance of Grade 91 steel alloy were evaluated in order to optimize the composition of the alloy to improve the creep resistance. The critical temperatures which are highlighted in this paper are Ac1 (the threshold temperature in which austinite begins to form), and Ac3 (the threshold temperature at which ferrite is fully transformed into austenite). Furthermore, optimization was presented through various Cr, V, Nb, and N concentrations in Gr.91 in relation to these critical temperatures and the mole fraction of M 23 C 6 , MX, and Z-Phase as critical secondary phases. Here, the results indicate that increasing V and Nb will increase MX stability, whereas decreasing Cr and N lead to a decrease in Z-Phase and M 23 C 6 stability, which may lead to an increased creep resistance of the material. Upon further analyzing the V, Nb, and N concentrations in Gr.91, results indicate that increasing Nb content in the steel can lead to an increased stability of Nb-rich MX2 carbide which can be used to replace Z-Phase in low N steels. Simulation results indicate that elimination of N with a dramatic increase in Nb concentrations result in the stability increase of only M 23 C 6 and MX2 phases at temperature regions between 600 °C and 1370 °C and a complete removal of Z-Phase precipitation. Overall, with the elimination of N, which destabilizes Z-Phase precipitation, and an increase in Nb for NbC carbide stability, a possible solution to increasing both long-term and short-term creep resistance for Gr.91 can be achieved, though further optimization and creep experiments need to be conducted for final conclusions.

36 MATERIALS SCIENCE↗

DOE OSTI2021

High-speed synchrotron X-ray phase-contrast imaging for evaluating microscale damage mechanisms and tracking cracking behaviors inside cross-ply GFRCs

In this study, we integrated the high-speed synchrotron X-ray phase-contrast imaging (PCI) with a modified Kolsky compression bar loading platform to visualize the dynamic failure processes of cross-ply glass fiber reinforced composites (GFRCs). Four S-2 glass/SC-15 composite specimens were prepared, having similar thicknesses but different stacking sequences, namely as [0 12 /90 12 ], [90 12 /0 12 ], [0 8 /90 8 /0 8 ], and [90 8 /0 8 /90 8 ]. Three-dimensional synchrotron X-ray computed tomography and scanning electron microscopy (SEM) were employed to examine the microstructures and quantify the fiber volume fractions. Each specimen was notched and subjected to a dynamic three-point flexural loading. The onset of cracking close to the notch tip, crack propagation in 0° or 90° plies and their interface, crack opening, and ultimately failure of the specimen were captured by high-speed synchrotron X-ray PCI. Additional dynamic experiments were performed to determine the average time when the stress wave propagated through the specimen and correlate the X-ray images with the specimen's force-deflection response. Finally, the surface morphology of each specimen after the dynamic loading was imaged by SEM. Comparison between real-time X-ray images and post-fracture SEM images demonstrated the capability of the X-ray method to record damage evolution inside composites. Furthermore, the high spatial and temporal resolutions of the X-ray setup and edge enhancement by PCI enabled the identification of microscale damage features within 1 μs. Two damaging processes were identified, crack growth was quantified, and fracture toughness of the composites was evaluated. The method is deemed useful to reveal microscale damage mechanisms and track cracking behaviors inside cross-ply GFRCs under dynamic loading in real time.

42 ENGINEERING↗

DOE OSTI2021

Evaluation of alkali–silica reaction damage in concrete using linear and nonlinear resonance techniques

Here in this study, the initiation and development of alkali–silica reaction (ASR) in concrete prisms containing reactive coarse (RCA) and reactive fine (RFA) aggregates were monitored over one year using linear and nonlinear resonance techniques. Although the linear resonance test could detect initiation and development of ASR damage in RCA specimens, it failed in the RFA specimens. Petrographic analysis confirmed the presence of early-stage ASR damage and the presence of different microcracking patterns in the RFA and RCA specimens, which may explain differences in the linear resonance data. For both RCA and RFA specimens, the nonlinear resonance test results were able to detect the initiation of ASR damage and showed a strong correlation with the ASR expansion for all specimens from different mix designs. The results demonstrate the high sensitivity of the nonlinear resonance test and its potential for quantitative evaluation of the ASR damage state of concrete specimens without a baseline measurement.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗

DOE OSTI2023

Exploration of imatinib and nilotinib-derived templates as the P2-Ligand for HIV-1 protease inhibitors: Design, synthesis, protein X-ray structural studies, and biological evaluation

Structure-based design, synthesis, X-ray structural studies, and biological evaluation of a new series of potent HIV-1 protease inhibitors are described. Here, these inhibitors contain various pyridyl-pyrimidine, aryl thiazole or alkylthiazole derivatives as the P2 ligands in combination with darunavir-like hydroxyethylamine sulfonamide isosteres. These heterocyclic ligands are inherent to kinase inhibitor drugs, such as nilotinib and imatinib. These ligands are designed to make hydrogen bonding interactions with the backbone atoms in the S2 subsite of HIV-1 protease. Various benzoic acid derivatives have been synthesized and incorporation of these ligands provided potent inhibitors that exhibited subnanomolar level protease inhibitory activity and low nanomolar level antiviral activity. Two high resolution X-ray structures of inhibitor-bound HIV-1 protease were determined. These structures provided important ligand-binding site interactions for further optimization of this class of protease inhibitors.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Design, synthesis, evaluation and X-ray structural studies of potent HIV-1 protease inhibitors containing substituted oxaspirocyclic carbamates as the P2 ligands

Here, we report here the design, synthesis and evaluation of a series of HIV-1 protease inhibitors that incorporate substituted oxaspirocyclic carbamate derivatives to serve as the P2 ligands. Various substituted ligand derivatives were synthesized in a racemic manner, using a tandem Prins/pinacol reaction as the key reaction. This reaction sets the relative stereochemistry of the oxaspirocyclic template in a highly diastereoselective manner. Reaction of the resulting ketone with enantiopure (S)-tert-butyl sulfinamide provided a convenient pathway to resolve the oxaspirocyclic ketone derivatives. The absolute stereochemical identity was determined by X-ray crystallography. The structure-activity studies demonstrate the effect of the stereochemistry of the oxaspirocyclic ring systems as well as the substitution effect on the aromatic ring. Several inhibitors exhibited potent HIV-1 protease inhibitory activity. One of these inhibitors displayed subnanomolar HIV-1 protease affinity and also exhibited potent antiviral activity. A high-resolution X-ray crystal structure of this inhibitor-bound HIV-1 protease show that the oxaspirocyclic P2 ligand forms an unconventional C–H⋯O bond with the backbone carboxyl group of Gly48’ and an interesting N–H … π interaction with the aromatic ring in the S2 subsite of HIV-1 protease active site.

Antiviral↗

DOE OSTI2022

Evaluating cascaded and tunable phase change materials for enhanced thermal energy storage utilization and effectiveness in building envelopes

The incorporation of phase change materials (PCMs) in envelope is considered an effective thermal energy storage (TES) method for energy savings and load flexibility in buildings. However, an important limitation of PCMs is their fixed and narrow transition temperature range. Because the interior temperature setpoints are typically different in summer versus winter, and the exterior temperature varies substantially above and below the setpoints during the year, PCMs with a fixed transition temperature are utilized only during part of the year. In this paper, we provide an extensive numerical analysis of the performance of a lightweight building envelope containing three different types of PCMs: traditional single-layer PCM with a fixed transition temperature, novel cascaded two-layer PCM with different transition temperatures, and a "futuristic" tunable PCM whose transition temperature can be varied in-situ using external excitation. We compare their performances by evaluating the relationship between the PCM utilization and parameters such as latent heat, transition temperature range, PCM thickness, and PCM location. While traditional PCMs are mostly active during one season, properly designed cascaded and tunable PCMs can be active much longer, thereby allowing load shift and energy savings in both heating and cooling seasons. Under the operating conditions considered in this study, tunable PCMs performed best, providing the highest utilization (about 2 times the traditional PCMs) and enhanced effectiveness (up to 99% peak load reduction in cooling season and 34% peak load reduction in heating season) with the same amount of material as the traditional PCMs; however, cascaded PCMs can be a good alternative while tunable PCMs are unavailable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

An evaluation of the demand response potential of integrated dynamic window and HVAC systems

Demand response (DR) increases the flexibility and reliability of the electricity grid as use of intermittent renewable energy sources increases. HVAC and envelope DR measures present the largest aggregate energy and peak demand savings potential of all commercial building end uses because their net demand savings occur during critical peak demand periods. Controllable envelope measures include switchable electrochromic windows, operable window attachments such as outdoor louvers, roller shades, and awnings, as well as other innovative facade technologies that can modulate both solar heat gain and daylight admission over a broad solar-optical range. This study evaluated the technical potential of DR-enabled dynamic windows to reduce critical peak demand for a prototypical medium office building situated in all 16 U.S. climates. Model predictive control (MPC) algorithms were designed to minimize electricity cost in daylit perimeter office zones through control of an electrochromic window with and without HVAC thermostat setpoint control. Conventional and time-of-use rates were used to shape the degree of DR. Median annual peak demand savings with window and thermostat control across all climate zones were 24.3 kW (4.4 W/m 2 ) per building or 15.9 W/m 2 for non-north perimeter zones. Resource adequacy at the whole building level was estimated to be 13.1 to 43.4 $/kW per year over the 30-year life of the installation. Co-benefits were increased energy efficiency, and reduced electricity cost and emissions. Visual and thermal comfort requirements were met at all times. Dynamic facades controlled by MPC have substantial technical potential for DR across all U.S. climates and warrant serious consideration for inclusion in DR portfolios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Methodology to evaluate design modifications intended to eliminate frosting and high discharge temperatures in air-source heat pumps (ASHPs) in cold climates

Air-source heat pumps (ASHPs) operating in cold climates experience problems with frosting and high refrigerant temperatures. These problems increase energy consumption, and their severity depends on the climatic conditions. In the present paper, a methodology for identifying the prevailing problem between frosting and high discharge temperatures is presented. Three performance indices, the frosting index (FI), the discharge index (DI), and the total loss index (TLI), are proposed to quantify the impacts of frosting and high discharge temperatures on the annual performance of ASHPs in different climatic conditions. The FI and DI show which problem (frosting or high discharge temperature) dominates, and the TLI indicates the combined effect of frosting and high discharge temperatures on the performance of an ASHP. A thermodynamic model of an ASHP coupled with the TRNSYS building simulation tool is used to estimate the performance of an ASHP and the proposed loss indices to estimate the impact of both frosting and high discharge temperatures for 45 cities in Canada. The results can be extended to other parts of the world that experience similar climatic conditions The results reveal that in cities in ASHRAE climatic zones 5 and 6 (classified as cold regions) where the ambient air temperatures are predominantly between -15 °C to 6 °C, ASHPs are heavily impacted by frosting. The problem of high discharge temperatures in ASHPs is predominant in cities in climate zones 7 and 8 (classified as very cold and subarctic regions) where the temperatures are frequently below -20 °C in winter. Among the cities considered, St. John, NL has the highest fraction of heating hours experiencing frosting (90 %), where the annual increase in energy consumption due to frosting is 13.5 % of the annual heating energy consumption. The highest annual increase in energy consumption due to high discharge temperatures is in Isachsen, NU (zone 8), where the increase is 30 % of the annual heating energy consumption. Based on the proposed indices, another index called the performance gain index (PGI) is created, which can be used as a first step to assess the energy-saving potential of design modifications applied to ASHPs to solve the problems of frosting and high discharge temperatures. The PGI will aid in developing climate specific ASHPs. One possible design modification is the use of a two-stage ASHP with an economizer. It is observed that the two-stage ASHP with economizer can mitigate high discharge temperatures and improve performance in very cold and subarctic regions (zones 7 and 8). However, it is not as beneficial in zones 5 and 6, where the impact of high discharge temperatures on performance is minimal and frosting dominates. Finally, a case study, using the PGI to evaluate the economic and environmental effectiveness of a two-stage ASHP with economizer is presented for the city of Saskatoon.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Performance evaluation of underground thermal storage integrated dual-source heat pump systems

The increasing demand for electricity stresses the existing electric grids. Buildings consume 73% of all U.S. electricity and are responsible for 30% of U.S. greenhouse gas emissions. Integrating thermal energy storage (TES) in building heating/cooling systems, which consume considerable electricity, can mitigate the challenges to electric grids. Here, this study reports on a novel thermal energy storage device integrated heat pump system to reshape the building electricity demand profile while maintaining thermal comfort. The annual performance of the proposed system has been evaluated through a dynamic system simulation with high fidelity in the Modelica platform. The dynamic model of the novel hybrid component named ‘dual purpose underground thermal battery’ was developed and validated. It was then incorporated into the system model. Given a time-of-use tariff, a rule-based control strategy was designed to shift the electric demand and switch the heat pump source for a typical single-family house in different climate zones of the United States. The system performance of the new TES-integrated dual-source heat pump was compared with that of a conventional air-source heat pump system. The results indicate that the proposed system can reduce the annual HVAC electricity cost by up to 52% while saving 45.2% on electricity consumption. In the Northern areas, the annual peak load of the HVAC system can be reduced by 64.9%. However, this reduction is less in the Southern areas as the system’s higher efficiency in winter dominates the overall energy-saving potential.

25 ENERGY STORAGE↗

DOE OSTI2024

Energy performance evaluation of the ASHRAE Guideline 36 control and reinforcement learning–based control using field measurements

This study evaluates the energy performance of ASHRAE Guideline 36–compliant control (ASHRAE 36 control) and reinforcement learning (RL)–based control through experimental field tests and a simulation study. Three field tests were conducted at Oak Ridge National Laboratory’s commercial building test facility in Oak Ridge, Tennessee: a baseline with a baseline conventional control, a test with ASHRAE 36 control, and a test with RL-based control. The selected ASHRAE 36 controls were trim and respond control, as well as variable air volume (VAV) box control. We compared the measured supply air temperature of the rooftop unit, VAV box supply air temperature, and VAV box supply airflow rate across the three test cases. The field data indicated that ASHRAE 36 controls operated as specified by ASHRAE Guideline 36. Based on these data, ASHRAE 36 control achieved a 45 % reduction in hourly averaged HVAC energy consumption compared with the baseline, and RL-based control achieved a 66 % reduction. These potential annual energy savings were confirmed using a calibrated whole-building energy model. Compared with the baseline, ASHRAE 36 control reduced HVAC energy consumption by 42 %, and RL-based control achieved a 54 % reduction. Furthermore, RL-based control reduced total HVAC energy consumption by 21 % more than ASHRAE 36 control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Evaluation of low-exergy heating and cooling systems and topology optimization for deep energy savings at the urban district level

District energy systems have the potential to achieve deep energy savings by leveraging the density and diversity of loads in urban districts. However, planning and adoption of district thermal energy systems is hindered by the analytical burden and high infrastructure costs. It is hypothesized that network topology optimization would enable wider adoption of advanced (ambient temperature) district thermal energy systems, resulting in energy savings. In this study, energy modeling is used to compare the energy performance of “conventional” and “advanced” district thermal energy systems at the urban district level, and a partial exhaustive search is used to evaluate a heuristic for the topology optimization problem. For the prototypical district considered, advanced district thermal energy systems mated with low-exergy building heating and cooling systems achieved a source energy use intensity that was 49% lower than that of conventional systems. The minimal spanning tree heuristic was demonstrated to be effective for the network topology optimization problem in the context of a prototypical district, and contributes to mitigating the problem’s computational complexity. The work presented in this paper demonstrates the potential of advanced district thermal energy systems to achieve deep energy savings, and advances to addressing barriers to their adoption through topology optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗