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At least 1,315 records · Page 73

Enhanced Tensile and Tear Toughness Properties of Thin-Wall Vacuum-Assisted High-Pressure Die-Cast Aural-5 Alloy by Friction Stir Processing

Steadily rising demand for glider weight reduction has driven the development of vacuum-assisted high-pressure die-cast (HPDC) Al-alloys for automotive structural components. Aural-5 is a strontium-modified HPDC alloy utilizing manganese (Mn) to reduce die soldering, eliminating detrimental needle-shaped Fe-bearing ß-phase intermetallic and improving ductility. HPDC Aural-5 contains shrinkage porosity, dendrites with Al-Si eutectic colonies, externally solidified crystals (ESCs), shear-band structure, and large second-phase particulates. Porosity, ESCs and large second-phase particles work as crack initiation sites, negatively impacting tensile properties. In this study, friction stir processing (FSP) is employed for microstructural modification of a thin-walled HPDC Aural-5 by eliminating porosity and breaking down dendrites, second-phase particles, eutectic colonies, ESCs and shear-band structures to create wrought microstructure with homogenized particle distribution. Mechanical property characterization indicates ~30% and ~35% enhancement in yield strength and ductility and associated marked effects on ~69% improvement in tear toughness according to the ASTM B871 test.

Friction stir processing, Aural-5, Strength, Tear ↗

Image processing methods for Rayleigh scattering measurements of diesel spray mixing at high repetition rate

This work describes the diagnostic implementation and image processing methods to quantitatively measure diesel spray mixing injected into a high-pressure, high-temperature environment. We used a high-repetition-rate pulse-burst laser developed in-house, a high-speed CMOS camera, and optimized the optical configuration to capture Rayleigh scattering images of the vaporized fuel jets inside a constant volume chamber. The experimental installation was modified to reduce reflections and flare levels to maximize the images’ signal-to-noise ratios by anti-reflection coatings on windows and surfaces, as well as series of optical baffles. Because of the specificities of the high-speed system, several image processing techniques had to be developed and implemented to provide quantitative fuel concentration measurements. We find that these methods involve various correction procedures such as camera linearity, laser intensity fluctuation, dynamic background flare, as well as beam-steering effects. Image inpainting was also applied to correct the Rayleigh scattering signal from large scatterers (e.g. particulates). The experiments demonstrate that applying planar laser Rayleigh scattering at high repetition rate to quantitatively resolve the mixing of fuel and ambient gases in diesel jets is challenging, but possible. The thorough analysis of the experimental uncertainty and comparisons to past data prove that such measurements can be accurate, whilst providing valuable information about the mixing processes of high-pressure diesel jets.

47 OTHER INSTRUMENTATION↗

A large nitrogen supply from the stable mineral-associated soil organic matter fraction

Soil organic matter (SOM) mineralization and nitrogen (N) release are key biogeochemical processes for which the relative contribution of particulate (POM) and mineral-associated organic matter (MAOM) fractions is poorly understood. MAOM is generally considered to be a more stable fraction that contains most of the soil organic N, whereas POM is more readily decomposable and contains less N. We measured variations in the potentially mineralizable N from each SOM fraction across three contrasting land uses (forest, pasture, and croplands) and two different grazing managements (rotational and continuous grazing). Contrary to expectations, we found that the MAOM fraction consistently supplied more N than the POM fraction during SOM mineralization in all land-uses evaluated. Across our environmental gradient, potentially mineralizable N from POM increased with the carbon (C) concentration and C/N ratio of POM, while potentially mineralizable N from MAOM increased with the C concentration of MAOM but decreased with clay content. Our work suggests that MAOM contributions to short-term N mineralization and N supply to plants have been undervalued.

54 ENVIRONMENTAL SCIENCES↗

Changes in soil pore structure generated by the root systems of maize , sorghum and switchgrass affect in situ N 2 O emissions and bacterial denitrification

Due to the heterogeneous nature of soil pore structure, processes such as nitrification and denitrification can occur simultaneously at microscopic levels, making prediction of small-scale nitrous oxide (N 2 O) emissions in the field notoriously difficult. We assessed N 2 O+N 2 emissions from soils under maize (Zea mays L.), switchgrass (Panicum virgatum L.), and energy sorghum (Sorghum bicolor L.), three potential bioenergy crops in order to identify the importance of different N 2 O sources to microsite production, and relate N 2 O source differences to crop-associated differences in pore structure formation. The combination of isotopic surveys of N 2 O in the field during one growing season and X-ray computed tomography (CT) enabled us to link results from isotopic mappings to soil structural properties. Further, our methodology allowed us to evaluate the potential for in situ N 2 O suppression by biological nitrification inhibition (BNI) in energy sorghum. Our results demonstrated that the fraction of N 2 O originating from bacterial denitrification and reduction of N 2 O to N 2 is largely determined by the volume of particulate organic matter occluded within the soil matrix and the anaerobic soil volume. Bacterial denitrification was greater in switchgrass than in the annual crops, related to changes in pore structure caused by the coarse root system. This led to high N-loses through N 2 emissions in the switchgrass system throughout the season a novel finding given the lack of data in the literature for total denitrification. Isotopic mapping indicated no differences in N 2 O-fluxes or their source processes between maize and energy sorghum that could be associated with the release of BNI by the investigated sorghum variety. The results of this research show how differences in soil pore structures among cropping systems can determine both N 2 O production via denitrification and total denitrification N losses in situ.

59 BASIC BIOLOGICAL SCIENCES↗

Mineral-Associated Organic Matter Concentration Beneath Northern Temperate Trees Varies by Mycorrhizal Type and Leaf Habit

Mycorrhizal fungi are important drivers of soil organic matter dynamics, but it can be difficult to isolate the effects of the fungi themselves from covarying traits of their host trees. For example, many trees with an evergreen leaf habit associate with ectomycorrhizal (ECM) fungi, while many deciduous tree species associate with arbuscular mycorrhizal (AM) fungi. Because leaf habit influences the quantity and quality of organic matter inputs to soil, it is often an important factor in soil carbon and nitrogen dynamics, and thus can mask the effects of mycorrhizal fungi on soil organic matter processes. We evaluated how tree mycorrhizal associations and leaf habit separately influence the amount and composition of mineral-associated organic matter (MAOM) and particulate organic matter (POM) in forest soils in New Hampshire and Vermont, USA. We measured carbon (C) and nitrogen (N) concentrations and C/N ratios of three soil density fractions beneath six tree species that vary in mycorrhizal association and leaf habit. We found lower concentrations of MAOM C and N beneath evergreen vs. deciduous trees, but only for tree species associating with AM fungi. Further, MAOM C/N was higher beneath evergreen trees and beneath trees with ECM fungi rather than AM fungi. Furthermore, these results add to the growing body of support for mycorrhizal fungi as mediators of soil organic matter dynamics, suggesting that the MAOM fraction is more sensitive to leaf habit beneath AM-associated versus ECM-associated trees. Because MAOM decomposition is thought to be less responsive than POM decomposition to changes in soil temperature and moisture, differences in the tendency of AM- and ECM-dominated forests to support MAOM formation and persistence may lead to systematic differences in the response of these forest types to ongoing climate change.

54 ENVIRONMENTAL SCIENCES↗

Impacts of climate and disturbance on nutrient fluxes and stoichiometry in mixed-conifer forests

Elucidating climatic impacts on stream nutrient export and stoichiometry will improve the understanding of forest carbon (C) storage in a warmer world. We constructed C, nitrogen (N), and phosphorus (P) budgets in four watersheds within a rain-snow transition site and another four within a higher-elevation, snow-dominated site, in California’s mixed-conifer zone. We used these two sites in a space-for-time substitution to assess the potential effects of warming on nutrient cycles in currently snow-dominated areas that will become more rain-dominated. During a non-drought period (water year (WY) 2004 – 2011), mean annual stream exports of C and N in particulate forms at the transition site were double that at the snow-dominated site, suggesting that sediment-associated nutrient losses may increase with warming. The transition site had 12% lower N but double the P content in mineral horizons, lower N:P mass ratios in organic horizons, and lower stream export of dissolved inorganic N than the snow-dominated site. Furthermore, these differences suggest that montane forests may receive lower supply of N relative to P with warming. In addition, given strong interests in forest thinning to increase drought resiliency, we examined changes in stream nutrient export after thinning and during a major drought period (WY 2013 – 2015). Stream exports of C, N, and P were similar between unthinned and thinned watersheds during drought, suggesting negligible thinning impacts on stream nutrient export during excessively dry periods. Taken together, our results suggest that as the climate warms, California’s montane forests may lose more nutrients through erosion and receive less N input than P.

54 ENVIRONMENTAL SCIENCES↗

Reduced accrual of mineral-associated organic matter after two years of enhanced rock weathering in cropland soils, though no net losses of soil organic carbon

Abstract Enhanced rock weathering (ERW), the application of crushed silicate rock to soil, can remove atmospheric carbon dioxide by converting it to (bi) carbonate ions or solid carbonate minerals. However, few studies have empirically evaluated ERW in field settings. A critical question remains as to whether additions of crushed rock might positively or negatively affect soil organic matter (SOM)—Earth’s largest terrestrial organic carbon (C) pool and a massive reservoir of organic nitrogen (N). Here, in three irrigated cropland field trials in California, USA, we investigated the effect of crushed meta-basalt rock additions on different pools of soil organic carbon and nitrogen (i.e., mineral-associated organic matter, MAOM, and particulate organic matter, POM), active microbial biomass, and microbial community composition. After 2 years of crushed rock additions, MAOM stocks were lower in the upper surface soil (0–10 cm) of plots with crushed rock compared to unamended control plots. At the 2 sites where baseline pre-treatment data were available, neither total SOC nor SON decreased over the 2 years of study in plots with crushed rock or unamended control plots. However, the accrual rate of MAOM-C and MAOM-N at 0–10 cm was lower in plots with crushed rock vs. unamended controls. Before ERW is deployed at large scales, our results suggest that field trials should assess the effects of crushed rock on SOM pools, especially over multi-year time scales and in different environmental contexts, to accurately assess changes in net C and understand the mechanisms driving interactions between ERW and SOM cycling.

58 GEOSCIENCES↗

Unlocking plant-microbial interactions in deep Mollisols in the Midwestern US: Linking depth gradients in roots, microbial activity, and soil carbon in agroecosystems

Deep-rooted plants may build soil carbon (C) stocks, but most research has focused on shallow soils, leaving gaps in our understanding of how shifts in the balance between decomposition and C inputs drive soil C accumulation with depth. Thus, our objectives were to: (1) link depth gradients in root biomass with microbial activity and soil C stocks down to 1 m, and (2) examine the potential of simple C inputs to prime soil C across depths. To this end, we dug 5 quantitative soil pits in Argiudolls under mature perennial miscanthus plots in the SoyFACE Farm (Champaign-Urbana, IL). We added 13 C labeled glucose to our soils to determine the fate of simple C inputs with depth. We found that fine root biomass, total soil C, mineral-associated organic C (MAOC), particulate organic C (POC), and microbial activity (as measured by potential enzyme activity) declined with depth. POC declined more rapidly than MAOC, resulting in an increase in the ratio of MAOC-to-POC. Root biomass, enzyme activity (either acid phosphatase or n-acetyl-glucosaminadase) activity, and microbial respiration explained 74% and 38% of the variability in soil total C and MAOC, respectively, while POC was dependent on root biomass and microbial respiration (47%). Although the incorporation of simple 13 C inputs into MAOC was similar across depths, these inputs led to greater net MAOC losses in shallow soils than in deeper soils between 50 and 100 cm. The divergent impact of simple C inputs across depths may suggest that MAOC in shallow soils is more susceptible to priming losses, while C inputs into deep soils may instead be more persistent. Collectively, our results suggest that depth gradients in soil C stocks represents a balance between inputs, decomposition, and microbial necromass production and that increases in root C inputs by deep-rooted plants may have the potential to build stable MAOC.

60 APPLIED LIFE SCIENCES↗

An introduction to the significance of sample size in particle analyses for nuclear forensics and radiological investigations

Particulate isotopic analysis in nuclear forensics has developed rapidly during the past two decades due to technical advances in determining the isotopic composition of individual particles. This paper introduces basic statistical concepts that can be applied by analysts to understand the importance of statistical adequacy when interpretating particle data. While these basic statistical methods provide a useful point-of-entry to particle data analysis, more sophisticated statistical and modeling approaches are needed to extract maximal information from such datasets in the future.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Well-to-wheels greenhouse gas and air pollutant emissions from battery electric vehicles in China

Electric vehicles (EVs) play a crucial role in addressing climate change and urban air quality concerns. China has emerged as the global largest EV market with 1.2 million EVs sold in 2018. This study established a novel life cycle energy use and emission inventory collecting up-to-date data including the electricity generation mix, emission controls in the power and industrial sectors, and the energy use in the fuel transport to estimate the well-to-wheels (WTW) greenhouse gas (GHG), and air pollutant emissions for battery electric vehicles (BEVs) and gasoline passenger vehicles in China. The results show that an average BEV has 35% lower WTW GHG emissions than an average gasoline car. BEVs reduce volatile organic compounds (VOCs) and nitrogen oxides (NOX) emissions by 98% and 34%, respectively, but have comparable or slightly higher primary fine particulate matter (PM2.5) and sulfur dioxide (SO2) emissions. Compact and small-size vehicles generally have lower GHG and air pollutant emissions than mid- and large-size vehicles. Class A vehicles contribute the most in the absolute amount of GHG and air pollutant emissions and therefore have the biggest potential for emission reduction. Our results suggest that global policymakers should continue to promote the transition to clean power sources, emission control, and fuel economy regulations, which are critical to enhancing emission mitigation benefits of BEVs. We also suggest EV development strategies should be formulated targeting vehicle class with the biggest emission mitigation potentials.

Air pollutant emissions↗

Trace elements and their isotopes in streams and rivers

The occurrence and speciation of trace elements in streams and rivers are controlled by interconnected hydrogeological, biogeochemical, and anthropogenic factors that include rock weathering, climate, vegetation, and land use within the watershed. This chapter provides a broad overview of trace element abundance, speciation, and mobility in streams and rivers, including an assessment of how trace elements are partitioned into dissolved, colloidal, and particulate phases. We also discuss how trace elements are mobilized into stream networks and transformed during transport. Select isotopic systems are reviewed to provide examples of how isotopic analyses can be used to understand geochemical and anthropogenic processes.

Herndon, Elizabeth [ORNL] (ORCID:0000000291945493)↗

Evolution of AISI 304L stainless steel part properties due to powder recycling in laser powder-bed fusion

Selective laser melting (SLM) is a powder-bed fusion process in Additive Manufacturing (AM) that uses a laser beam to selectively fuse layers of powder into near net-shape components with little porosity. However, inconsistencies in the part properties due to the presence of defects in as-built components has hindered the widespread adoption of SLM for industrial applications forcing researchers to study the sources of variation for quality control purposes. A critical area suspected of creating variation in the part properties is the feedstock, where batch-to-batch differences as well as changes in the powder properties with reuse have the potential to affect performance. During processing, laser spatter and condensate eject from the melt pool and deposit into the powder-bed surrounding the parts. These particulates, more commonly known as ejecta, differ morphologically and chemically from the virgin powder compromising its reusability. In this study, 304L stainless steel powder was recycled for a total of 5 times through a systematic approach aimed at accelerating powder degradation to reveal the influence on both the tensile and impact toughness properties. Through analysis of variance (ANOVA), it was found that tensile properties did not change with reuse, while the impact toughness showed a steady decline illustrating the differences in static and dynamic part properties due to powder recycling.

36 MATERIALS SCIENCE↗

Bayesian modeling of traffic-related air pollutants: A case study of urban transportation and air quality dynamics in Columbia, South Carolina

Traffic emissions significantly impact near-road air quality and public health. This research applies a Bayesian modeling framework to investigate these impacts using high-resolution traffic and air pollutant data from an urban corridor in Columbia, South Carolina. Despite a data collection period truncated by the COVID-19 lockdown, the Bayesian approach successfully identified significant predictors and quantified model uncertainty. Employing Bayesian Model Selection and Averaging enhanced prediction accuracy and evaluated model uncertainty. Findings indicate that higher temperatures and increased moisture levels elevate particulate matter (PM 1.0 , PM 2.5 , PM 10 ) concentrations, while traffic speed significantly affects nitrogen dioxide (NO 2 ) levels. Specifically, higher average traffic speeds (indicative of smoother flow) correspond to lower NO 2 concentrations, suggesting that less congested conditions reduce NO 2 emissions. This study highlights the robustness of Bayesian methods for generating reliable air quality insights even under data-constrained conditions. The findings underscore the importance of traffic flow management (e.g., reducing congestion) for mitigating near-road NO 2 exposure and provide a basis for developing targeted public health strategies.

54 ENVIRONMENTAL SCIENCES↗

Estimating source-sink distributions and fluxes of reactive nitrogen and sulfur within a mixed forest canopy

The vertical source-sink distribution of air pollutants within and above forested canopies is necessary for describing the biological, physical, and chemical processes influencing the soil-vegetation-atmosphere exchange. Here, this study implemented inverse modeling methods to estimate the source-sink and flux profiles of reactive nitrogen (N) and sulfur (S) compounds from measurements of the mean concentration profiles of ammonia (NH 3 ), nitric acid (HNO 3 ), sulfur dioxide (SO 2 ), and particulate ammonium (NH 4 + ), nitrate (NO 3 − ), and sulfate (SO 4 2− ) at a forest site in the southern Appalachian Mountains. Three inverse approaches utilizing different approximations to scalar transport within the canopy were developed and evaluated against sensible heat flux measurements. The Eulerian model (EUL), which incorporates vertical velocity skewness, performed well in reproducing the turbulent heat fluxes and was subsequently used to calculate the chemical source-sink and flux profiles. Above-canopy fluxes of NH 3 were downward, indicating that the forest was a net sink of NH 3 . The soil/litter layer was both a source and a sink for NH 3 but the exchange rate at the forest floor was small. Fluxes of HNO 3 , SO 2 , NO 3 − , NH 4 + , and SO 4 2- were uni-directional (deposition only) between the air and the canopy/ground and increased monotonically from the forest floor to the canopy top. Crown foliage dominated the uptake of reactive N and S during the growing season, accounting for 80–90% of the total canopy-scale flux. Fluxes and canopy-ground partitioning estimated using the resistance-based Surface Tiled Aerosol and Gas Exchange (STAGE) model were generally comparable to EUL. The comparison highlights the need for improved parameterizations of litter exchange and NH 3 compensation points in resistance models for forest ecosystems. The findings here benefit the application of critical loads in forest ecosystems and guide further development of resistance-based exchange models.

54 ENVIRONMENTAL SCIENCES↗

Pigment modulation in response to irradiance intensity in the fast-growing alga Picochlorum celeri

Picochlorum celeri has among the fastest photoautotrophic growth rates (~2 h doubling time in optimal conditions) reported to date for a marine alga. This study comprehensively analyzes the levels of Picochlorum celeri photosynthetic pigments, which can reach up to ~13% of the total particulate organic carbon (POC) under light-limiting conditions. The main Picochlorum celeri pigments identified include: chlorophyll a, chlorophyll b, lutein, β-carotene, canthaxanthin, violaxanthin, neoxanthin, zeaxanthin and antheraxanthin. The ketocarotenoid canthaxanthin can accumulate up to 120 mg L -1 in Picochlorum celeri liquid culture; ~12% of it was found in an extracellular polysaccharide matrix. Using a solar-simulating automated photobioreactor, we monitor the photoacclimation of cultures maintained in unshaded conditions (<0.5 μg mL -1 of total chlorophyll) through transitions from high irradiance (1000 μmoles photosynthetically active radiation (PAR) m -2 s -1 ) to low irradiance (60 μmoles PAR m -2 s -1 ), and conversely from low to high irradiance. Canthaxanthin and zeaxanthin accumulation are among the most rapid modulation responses when cultures are shifted from low to high irradiance. The violaxanthin, antherazanthin, and zeaxanthin (VAZ) pool is ~3-fold higher in high-light cultures, suggesting that the VAZ cycle combined with a dramatic reduction in chlorophyll levels are among the major mechanisms used in Picochlorum celeri to efficiently acclimate to high-irradiance levels. Responsive pigment modulation was also observed in denser cultures (~0.65 g L –1 ) grown under a diel cycle (pond-mimicking conditions). Furthermore, this research provides unique insights into the dynamics of pigment modulation and photoacclimation in response to changing irradiance in a biotechnologically promising alga and will inform future pigment engineering strategies to further improve light capture and biomass accumulation.

59 BASIC BIOLOGICAL SCIENCES↗

Experimental study and demonstration of pilot-scale, dry feed, oxy-coal combustion under pressure

In this paper, we discuss how pressurized oxy-combustion is a promising technology for low-carbon, fossil fuel utilization. It has the potential of improved efficiency and economics compared with conventional atmospheric pressure oxy-combustion. Washington University in St. Louis has proposed a new pressurized oxy-combustion process, namely Staged Pressurized Oxy-Combustion, which has the potential to improve further the plant efficiency, operational flexibility, and economics. This process burns pulverized coal in a pressurized, oxy-combustion environment, which has not been demonstrated in a pilot-scale system before. To address this gap, a 100 kWth pressurized oxy-combustion facility was designed and constructed. This facility has a unique burner and furnace design featuring a co-axial, low-mixing flow field, which is drastically different from conventional coal-fired boiler designs where strong mixing is sought by introducing swirl or recirculating flows. This work aims to present the first pilot-scale experimental results of a dry-feed, pressurized oxy-combustion system. The tests focused on exploring flame stability and shape, char burnout, and fine particulate matter formation. Testing results suggest that the burner has excellent flame stability. The flame shape is consistent with the design philosophy and agrees with large eddy simulations. Importantly, complete char combustion can be achieved with an oxygen mole fraction in the flue gas of only 0.8%, as opposed to a required value of ~3% for conventional atmospheric pressure air-fired or oxyfuel combustion, which reduces the costs of both oxygen generation upstream and oxygen removal downstream. The testing results show promise for dry-feed, pressurized oxy-combustion, and the new burner and furnace design.

01 COAL, LIGNITE, AND PEAT↗

Evaluating the impact of wildfire smoke on solar photovoltaic production

There are growing needs to understand how extreme weather events impact the electrical grid. Renewable energy sources such as solar photovoltaics are expanding in use to help sustainably meet electricity demands. Wildfires and, notably, the widespread smoke resulting from them, are one such extreme event that can impair the performance of solar photovoltaics. However, isolating the impact that smoke has on photovoltaic energy production, separate from ambient conditions, can be difficult. In this work, we seek to understand and quantify the impacts of wildfire smoke on solar photovoltaic production within the Western United States. Our analysis focuses on the construction of a random forest regression model to predict overall solar photovoltaic production. The model is used to separate and quantify the impacts of wildfire smoke in particular. To do so, we fuse historical weather, solar photovoltaic energy production, and PM2.5 particulate matter (primary smoke pollutant) data to train and test our model. The additional weather data allows us to capture interactions between wildfire smoke and other ambient conditions, as well as to create a more powerful predictive model capable of better quantifying the impacts of wildfire smoke on its own. We find that solar PV energy production decreases 8.3% on average during high smoke days at PV sites as compared to similar conditions without smoke present. Finally, this work allows us to improve our understanding of the potential impact on photovoltaic-based energy production estimates due to wildfire events and can help inform grid and operational planning as solar photovoltaic penetration levels continue to grow.

14 SOLAR ENERGY↗

Deep reinforcement learning control for co-optimizing energy consumption, thermal comfort, and indoor air quality in an office building

With the recent demand for decarbonization and energy efficiency, advanced HVAC control using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible structures, DRL has been successful in energy reduction for many HVAC systems. However, only a few researches applied DRL agents to manage the entire central HVAC system and control multiple components in both the water loop and the air loop, owing to its complex system structures. Moreover, those researches have not extended their applications by incorporating the indoor air quality, especially both CO2 and PM2.5concentrations, on top of energy saving and thermal comfort, as achieving those objectives simultaneously can cause multiple control conflicts. What's more, DRL agents are usually trained on the simulation environment before deployment, so another challenge is to develop an accurate but relatively simple simulator. Therefore, we propose a DRL algorithm for a central HVAC system to co-optimize energy consumption, thermal comfort, indoor CO2 level, and indoor PM2.5 level in an office building. To train the controller, we also developed a hybrid simulator that decoupled the complex system into multiple simulation models, which are calibrated separately using laboratory test data. The hybrid simulator combined the dynamics of the HVAC system, the building envelope, as well as moisture, CO2, and particulate matter transfer. Three control algorithms (rule-based, MPC, and DRL) are developed, and their performances are evaluated on the hybrid simulator environment with a realistic scenario (i.e., with stochastic noises). The test results showed that, the DRL controller can save 21.4 % of energy compared to a rule-based controller, and has improved thermal comfort, reduced indoor CO2 concentration. The MPC controller showed an 18.6 % energy saving compared to the DRL controller, mainly due to savings from comfort and indoor air quality boundary violations caused by unmeasured disturbances, and it also highlights computational challenges in real-time control due to non-linear optimization. Finally, we provide the practical considerations for designing and implementing the DRL and MPC controllers based on their respective pros and cons.

Guo, Fangzhou↗