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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Improved Characterization of Soil Organic Matter by Integrating FT-ICR MS, Liquid Chromatography Tandem Mass Spectrometry, and Molecular Networking: A Case Study of Root Litter Decay under Drought Conditions

Understanding of how soil organic matter (SOM) chemistry is altered in a changing climate has advanced considerably; however, most SOM components remain unidentified, impeding the ability to characterize a major fraction of organic matter and predict what types of molecules, and from which sources, will persist in soil. Here we present a novel approach to better characterize SOM extracts by integrating information from three types of analyses, and we deploy this method to characterize decaying root-detritus soil microcosms subjected to either drought or normal conditions. To observe broad differences in composition, we employed direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). We complemented this with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify components by library matching. Since libraries contain only a small fraction of SOM components, we also used fragment spectral cosine similarity scores to relate unknowns and library matches through molecular networks. This integrated approach allowed us to corroborate DI-FT-ICR MS molecular formulas using library matches, which included fungal metabolites and related polyphenolic compounds. We also inferred structures of unknowns from molecular networks and improved LC-MS/MS annotation rates from ~5 to 35% by considering DI-FT-ICR MS molecular formula assignments. Under drought conditions, we found greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas and lower average nominal oxidation state of carbon, suggesting reduced decomposition of SOM and/or microbes under stress. Our integrated approach provides a framework for enhanced annotation of SOM components that is more comprehensive than performing individual data analyses in parallel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The Influence of Land‐Surface Conditions on the 2020–2021 Western US Drought

Abstract In summer 2021, 90% of the western United States (WUS) experienced drought, with over half of the region facing extreme or exceptional conditions, leading to water scarcity, crop loss, ecological degradation, and significant socio‐economic consequences. Beyond the established influence of oceanic forcing and internal atmospheric variability, this study highlights the importance of land‐surface conditions in the development of the 2020–2021 WUS drought, using observational data analysis and novel numerical simulations. Our results demonstrate that the soil moisture state preceding a meteorological drought, due to its intrinsic memory, is a critical factor in the development of soil droughts. Specifically, wet soil conditions can delay the transition from meteorological to soil droughts by several months or even nullify the effects of La Niña‐driven meteorological droughts, while drier conditions can exacerbate these impacts, leading to more severe soil droughts. For the same reason, soil droughts can persist well beyond the end of meteorological droughts. Our numerical experiments suggest a relatively weak soil moisture‐precipitation coupling during this drought period, corroborating the primary contributions of the ocean and atmosphere to this meteorological drought. Additionally, drought‐induced vegetation losses can mitigate soil droughts by reducing evapotranspiration and slowing the depletion of soil moisture. This study highlights the importance of soil moisture and vegetation conditions in seasonal‐to‐interannual drought predictions. Findings from this study have implications for regions like the WUS, which are experiencing anthropogenically‐driven soil aridification and vegetation greening, suggesting that future soil droughts in these areas may develop more rapidly, become more severe, and persist longer.

Jiang, Yelin [Lamont‐Doherty Earth Observatory Col↗
NASA NTRS2014

Using Satellite Imagery to Identify Tornado Damage Tracks and Recovery from the April 27, 2011 Severe Weather Outbreak

Emergency response to natural disasters requires coordination between multiple local, state, and federal agencies. Single, relatively weak tornado events may require comparatively simple response efforts; but larger "outbreak" events with multiple strong, long-track tornadoes can benefit from additional tools to help expedite these efforts. Meteorologists from NOAA's National Weather Service conduct field surveys to map tornado tracks, assess damage, and determine the tornado intensity following each event. Moderate and high resolution satellite imagery can support these surveys by providing a high-level view of the affected areas. Satellite imagery could then be used to target areas for immediate survey or to corroborate the results of the survey after it is completed. In this study, the feasibility of using satellite imagery to identify tornado damage tracks was determined by comparing the characteristics of tracks observed from low-earth orbit to tracks assessed during the official NWS storm survey process. Of the 68 NWS confirmed centerlines, 24 tracks (35.3%) could be distinguished from other surface features using satellite imagery. Within each EF category, 0% of EF-0, 3% of EF-1, 50% of EF-2, 77.7% of EF-3, 87.5% of EF-4 and 100% of EF-5 tornadoes were detected. It was shown that satellite data can be used to identify tornado damage tracks in MODIS and ASTER NDVI imagery, where damage to vegetation creates a sharp drop in values though the minimum EF-category which can be detected is dependent upon the type of sensor used and underlying vegetation. Near-real time data from moderate resolution sensors compare favorably to field surveys after the event and suggest that the data can provide some value in the assessment process.

Cole, Tony A.↗
NASA NTRS2014

Using Satellite Imagery to Identify Tornado Damage Tracks and Recovery from the April 27, 2011 Severe Weather Outbreak

Emergency response to natural disasters requires coordination between multiple local, state, and federal agencies. Single, relatively weak tornado events may require comparatively simple response efforts; but larger "outbreak" events with multiple strong, long-track tornadoes can benefit from additional tools to help expedite these efforts. Meteorologists from NOAA's National Weather Service conduct field surveys to map tornado tracks, assess damage, and determine the tornado intensity following each event. Moderate and high resolution satellite imagery can support these surveys by providing a high-level view of the affected areas. Satellite imagery could then be used to target areas for immediate survey or to corroborate the results of the survey after it is completed. In this study, the feasibility of using satellite imagery to identify tornado damage tracks was determined by comparing the characteristics of tracks observed from low-earth orbit to tracks assessed during the official NWS storm survey process. Of the 68 NWS confirmed centerlines, 24 tracks (35.3%) could be distinguished from other surface features using satellite imagery. Within each EF category, 0% of EF-0, 3% of EF-1, 50% of EF-2, 77.7% of EF-3, 87.5% of EF-4 and 100% of EF-5 tornadoes were detected. It was shown that satellite data can be used to identify tornado damage tracks in MODIS and ASTER NDVI imagery, where damage to vegetation creates a sharp drop in values though the minimum EF-category which can be detected is dependent upon the type of sensor used and underlying vegetation. Near-real time data from moderate resolution sensors compare favorably to field surveys after the event and suggest that the data can provide some value in the assessment process.

Molthan, Andrew L.↗
NASA NTRS1999

Investigation of Tropical Transport with UARS Data

Measurements of trace constituents obtained by instruments aboard the Upper Atmosphere Research Satellite (UARS) have been used to study transport processes associated with the quasi-biennial oscillation, laterally propagating Rossby waves, and upward propagating Kelvin waves in the tropical and subtropical upper troposphere and stratosphere. Mean vertical motions, vertical diffusivities and in-mixing rates were inferred from observations of the 'tape recorder' signal in near-equatorial stratospheric water vapor. The effect of the quasi-biennial oscillation (QBO) on tracer distributions in the upper half of the stratosphere was seen in a spectacular 'staircase' pattern, predominantly in the winter hemisphere, revealing the latitudinally asymmetric nature of QBO transport due to induced mean meridional circulations and modulation of lateral mixing associated with planetary Rossby waves. The propagation of Rossby waves across the equator in the westerly phase of the QBO was seen in tracer fields and corroborating United Kingdom Meteorological Office (UKMO) analyses; a modeling study of the effect of these waves on typical QBO wind profiles was performed. Water vapor in the upper troposphere and lower stratosphere was found to exhibit signatures of the tropical intraseasonal oscillation (TIO) and faster Kelvin waves in the two regions, respectively.

Dunkerton, Timothy J.↗
NASA NTRS2014

Far-Reaching Impacts of African Dust- A Calipso Perspective

African dust can transport across the tropical Atlantic and reach the Amazon basin, exerting far-reaching impacts on climate in downwind regions. The transported dust influences the surface-atmosphere interactions and cloud and precipitation processes through perturbing the surface radiative budget and atmospheric radiative heating and acting as cloud condensation nuclei and ice nuclei. Dust also influences biogeochemical cycle and climate through providing nutrients vital to the productivity of ocean biomass and Amazon forests. Assessing these climate impacts relies on an accurate quantification of dust transport and deposition. Currently model simulations show extremely large diversity, which calls for a need of observational constraints. Kaufman et al. (2005) estimated from MODIS aerosol measurements that about 144 Tg of dust is deposited into the tropical Atlantic and 50 Tg of dust into the Amazon in 2001. This estimated dust import to Amazon is a factor of 3-4 higher than other observations and models. However, several studies have argued that the oversimplified characterization of dust vertical profile in the study would have introduced large uncertainty and very likely a high bias. In this study we quantify the trans-Atlantic dust transport and deposition by using 7 years (2007-2013) observations from CALIPSO lidar. CALIPSO acquires high-resolution aerosol extinction and depolarization profiles in both cloud-free and above-cloud conditions. The unique CALIPSO capability of profiling aerosols above clouds offers an unprecedented opportunity of examining uncertainties associated with the use of MODIS clear-sky data. Dust is separated from other types of aerosols using the depolarization measurements. We estimated that on the basis of 7-year average, 118142 Tg of dust is deposited into the tropical Atlantic and 3860 Tg of dust into the Amazon basin. Substantial interannual variations are observed during the period, with the maximum to minimum ratio of about 1.6 and 2.5 for the deposition to the tropical Atlantic and Amazon, respectively. The MODIS-based estimates appear to fall within the range of CALIPSO-based estimates; and the difference between MODIS and CALIPSO estimates can be largely attributed to the interannual variability, which is corroborated by long-term surface dust concentration observations in the tropical Atlantic. Considering that CALIPSO generally tends to underestimate the aerosol loading, our estimate is likely to represent a low bound for the dust transport and deposition estimate. The finding suggests that models have substantial biases and considerable effort is needed to improve model simulations of dust cycle.

dust↗
NASA NTRS2019

Diurnal and Seasonal Variations in Chlorophyll Fluorescence Associated with Photosynthesis at Leaf and Canopy Scales

There is a critical need for sensitive remote sensing approaches to monitor the parameters governing photosynthesis, at the temporal scales relevant to their natural dynamics. The photochemical reflectance index (PRI) and chlorophyll fluorescence (F) offer a strong potential for monitoring photosynthesis at local, regional, and global scales, however the relationships between photosynthesis and solar induced F (SIF) on diurnal and seasonal scales are not fully understood. This study examines how the fine spatial and temporal scale SIF observations relate to leaf level chlorophyll fluorescence metrics (i.e., PSII yield, YII and electron transport rate, ETR), canopy gross primary productivity (GPP), and PRI. The results contribute to enhancing the understanding of how SIF can be used to monitor canopy photosynthesis. This effort captured the seasonal and diurnal variation in GPP, reflectance, F, and SIF in the O2A (SIFA) and O2B (SIFB) atmospheric bands for corn (Zea mays L.) at a study site in Greenbelt, MD. Positive linear relationships of SIF to canopy GPP and to leaf ETR were documented, corroborating published reports. Our findings demonstrate that canopy SIF metrics are able to capture the dynamics in photosynthesis at both leaf and canopy levels, and show that the relationship between GPP and SIF metrics differs depending on the light conditions (i.e., above or below saturation level for photosynthesis). The sum of SIFA and SIFB (SIFA+B), as well as the SIFA+B yield, captured the dynamics in GPP and light use efficiency, suggesting the importance of including SIFB in monitoring photosynthetic function. Further efforts are required to determine if these findings will scale successfully to airborne and satellite levels, and to document the effects of data uncertainties on the scaling.

Campbell, Petya K.↗
DOE OSTI2026

Er Al :Al 2 ⁢O 3 for telecom-band photonics: Electronic structure and optical properties

Er-doped Al 2 ⁢O 3 is a promising host for telecom-band integrated photonics. Here, in this study, we combine ab initio calculations with a symmetry-resolved analysis to elucidate substitutional Er on the Al site (Er Al ) in 𝛼−Al 2 ⁢O 3 . First-principles relaxations confirm the structural stability of Er Al . We then use the local trigonal crystal-field symmetry to classify the Er-derived impurity levels by irreducible representations and to derive polarization-resolved electric-dipole selection rules, explicitly identifying the symmetry-allowed 𝑓−𝑑 hybridization channels. Kubo-Greenwood absorption spectra computed from Kohn-Sham states quantitatively corroborate these symmetry predictions. Furthermore, we connect the calculated intra-4⁢𝑓 line strengths to Judd-Ofelt theory, clarifying the role of 4⁢𝑓−5⁢𝑑 admixture in enabling optical activity. Notably, we predict a characteristic absorption near 1.47 µ⁢m (telecom band), relevant for on-chip amplification and emission. To our knowledge, a symmetry-resolved first-principles treatment of Er:Al 2 ⁢O 3 with an explicit Judd-Ofelt interpretation has not been reported, providing a transferable framework for tailoring rare-earth dopants in wide-band-gap oxides for integrated photonics. Our results for the optical spectra are in good agreement with experimental data. The resulting symmetry-based selection rules translate directly to polarization-dependent coupling in Al 2 ⁢O 3 integrated photonic waveguides and resonators, enabling device-level design of TE/TM-mode interaction with Er emitters in the 1.5-µ⁢m telecom band.

Er-doped Al2O3↗
NASA NTRS1992

Radiometric calibration and atmospheric correction of satellite and aircraft data for FIFE

The satellite and aircraft radiometric calibration and atmospheric correction work carried out as part of the first International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) are summarized. A large volume (120 Gbytes) of radiometric data were acquired and derived from a number of different instruments on a variety of platforms. The same basic procedure was applied to each instrument: derive the most recent calibration coefficients for converting sensor counts to reflective spectral radiances; correct the radiances for earth-sun distance variations and incident solar spectral irradiance within the bandpass of each respective instrument channel at the top of the atmosphere; characterize the atmosphere for aerosols and absorbing gases; and derive apparent surface reflectance by correcting the exoatmospheric values for atmospheric attenuation. The same basic approach was used for surface temperature derivation. The results of this processing were verified by surface measurements, and corroborated by sensor intercomparisons.

Goetz, Scott J.↗
NASA NTRSDate not supplied

Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)

The Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which controls the sources sinks and chemistry within the Goddard Earth Observing System, recently underwent a major refactoring and update to the representation of physical processes. The code refactoring increases flexibility such multiple instances of an aerosol species can be run and interact with radiation and cloud microphysics, in addition to the output of multiple wavelength aerosol optical properties in support of data assimilation. From a science perspective, a new radiatively active tracer, brown carbon, was added to distinguish smoke from other sources of organic aerosol thereby improving optical properties entering the radiative calculations. A four-year benchmark simulation was evaluated using in situ and space borne measurements to develop a baseline and prioritize future development. A comparison of simulated aerosol optical depth between GOCART-2G and MODIS retrievals indicates the model captures the overall spatial pattern and seasonal cycle of aerosol optical depth but overestimates aerosol extinction over dusty regions and underestimates aerosol extinction over northern hemisphere boreal forests, requiring further tuning of emissions. This MODIS-based analysis is corroborated by comparisons to MISR and selected AERONET stations. Despite the underestimate of aerosol optical depth in biomass burning regions in GEOS, there is an overestimate in the surface mass of organic carbon in the United States, especially during the summer months.

Allison Collow↗
NASA NTRS2024

Benchmarking GOCART-2G in the Goddard Earth Observing System (GEOS)

The Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which controls the sources sinks and chemistry within the Goddard Earth Observing System, recently underwent a major refactoring and update to the representation of physical processes. This paper serves to document code changes that were included in GOCART 2nd Generation (GOCART-2G) and establishes a benchmark simulation that is to be used for future development of the system. The code refactoring increases flexibility such multiple instances of an aerosol species can be run and interact with radiation and cloud microphysics, in addition to the output of multiple wavelength aerosol optical properties in support of data assimilation. From a science perspective, a new radiatively active tracer, brown carbon, was added to distinguish smoke from other sources of organic aerosol thereby improving optical properties entering the radiative calculations. A four-year benchmark simulation was evaluated using in situ and space borne measurements to develop a baseline and prioritize future development. A comparison of simulated aerosol optical depth between GOCART-2G and MODIS retrievals indicates the model captures the overall spatial pattern and seasonal cycle of aerosol optical depth but overestimates aerosol extinction over dusty regions and underestimates aerosol extinction over northern hemisphere boreal forests, requiring further tuning of emissions. This MODIS-based analysis is corroborated by comparisons to MISR and selected AERONET stations. Despite the underestimate of aerosol optical depth in biomass burning regions in GEOS, there is an overestimate in the surface mass of organic carbon in the United States, especially during the summer months.

Allison B Collow↗
DOE OSTI2025

SVM-Based Synchronized Fault Detection for 100% Renewable Microgrids

Traditional protection schemes face significant challenges when applied to microgrids with high penetrations of renewables with inverter-based resources (IBRs). The proliferation of advanced sensing and communication technologies has generated copious data, offering an opportunity to overcome these limitations using data-driven machine learning approaches. This work proposes a novel approach based on a support vector machine (SVM) for detecting faults within a 100% renewable microgrid. The approach encompasses a systematic offline training stage for the development of a linear SVM-based fault detection algorithm. This process covers offline data collection from the microgrid under study, the extraction of features such as positive- and negative-sequence components and the total harmonic distortion of the voltage and current measurements of the relays, and the design of the linear SVM-based classifier. During the online implementation, however, different classifiers can exhibit asynchronicity in detecting the fault inception at different subcycle-to-cycle period-level delays. To circumvent this asynchronicity issue, a separate algorithm is developed for each relay to estimate the fault inception time as close to the real fault time. The performance of the proposed SVM-based synchronized fault detection method is evaluated using online time-domain simulation studies on a microgrid test system. The results corroborate the reliability of the fault detection scheme when tested under various fault cases (fault types, locations, and impedances) and non-fault cases during both grid-tied and islanded operation modes.

100% microgrid↗
DOE OSTI2024

SVM-Based Synchronized Fault Detection for 100% Renewable Microgrids: Preprint

Traditional protection schemes face significant challenges when applied to microgrids with high penetrations of renewables with inverter-based resources (IBRs). The proliferation of advanced sensing and communication technologies has generated copious data, offering an opportunity to overcome these limitations using data-driven machine learning approaches. This work proposes a novel approach based on a support vector machine (SVM) for detecting faults within a 100% renewable microgrid. The approach encompasses a systematic offline training stage for the development of a linear SVM-based fault detection algorithm. This process covers offline data collection from the microgrid under study, the extraction of features such as positive- and negative-sequence components and the total harmonic distortion of the voltage and current measurements of the relays, and the design of the linear SVM-based classifier. During the online implementation, however, different classifiers can exhibit asynchronicity in detecting the fault inception at different subcycle-to-cycle period-level delays. To circumvent this asynchronicity issue, a separate algorithm is developed for each relay to estimate the fault inception time as close to the real fault time. The performance of the proposed SVM-based synchronized fault detection method is evaluated using online time-domain simulation studies on a microgrid test system. The results corroborate the reliability of the fault detection scheme when tested under various fault cases (fault types, locations, and impedances) and non-fault cases during both grid-tied and islanded operation modes.

100% microgrid↗
DOE OSTI2024

Multidimensional Rietveld refinement of high-pressure neutron diffraction data of PbNCN

High-pressure neutron powder diffraction data from PbNCN were collected on the high-pressure diffraction beamline SNAP located at the Spallation Neutron Source (SNS) of Oak Ridge National Laboratory (Tennessee, USA). The diffraction data were analyzed using the novel method of multidimensional (two dimensions for now, potentially more in the future) Rietveld refinement and, for comparison, employing the conventional Rietveld method. To achieve two-dimensional analysis, a detailed description of the SNAP instrument characteristics was created, serving as an instrument parameter file, and then yielding both cell and spatial parameters as refined under pressure for the first time for solid-state cyanamides/carbodiimides. The bulk modulus B 0 = 25.1 (15) GPa and its derivative B ′ 0 = 11.1 (8) were extracted for PbNCN following the Vinet equation of state. Surprisingly, an internal transition was observed beyond 2.0 (2) GPa, resulting from switching the bond multiplicities (and bending direction) of the NCN 2− complex anion. The results were corroborated using electronic structure calculation from first principles, highlighting both local structural and chemical bonding details.

Meinerzhagen, Yannick↗
NASA NTRS2004

Comparison Between Lidar and Nephelometer Measurements of Aerosol Hygroscopicity at the Southern Great Plains Atmospheric Radiation Measurement Site

Aerosol hygroscopicity has a significant effect on radiative properties of aerosols. Here a lidar method, applicable to cloud-capped, well-mixed atmospheric boundary layers, is employed to determine the hygroscopic growth factor f(RH) under unperturbed, ambient atmospheric conditions. The data used for the analysis were collected under a wide range of atmospheric aerosol levels during both routine measurement periods and during the intensive operations period (IOP) in May 2003 at the Southern Great Plains (SGP) Climate Research Facility in Oklahoma, USA, as part of the Atmospheric Radiation Measurement (ARM) program. There is a good correlation (approx. 0.7) between a lidar-derived growth factor (measured over the range 85% RH to 96% RH) with a nephelometer-derived growth factor measured over the RH range 40% to 85%. For these RH ranges, the slope of the lidar-derived growth factor is much steeper than that of the nephelometer-derived growth factor, reflecting the rapid increase in particle size with increasing RH. The results are corroborated by aerosol model calculations of lidar and nephelometer equivalent f(RH) based on in situ aerosol size and composition measurements during the IOP. It is suggested that the lidar method can provide useful measurements of the dependence of aerosol optical properties on relative humidity, and under conditions closer to saturation than can currently be achieved with humidified nephelometers.

Pahlow, M.↗
DOE OSTI2026

Reassessing Hybrid Vigor or Hybrid Dysfunction Using Physiological Trade-Offs in an Endangered Salamander System

Fitness of interspecific hybrids can be higher or lower than that of their parental genotypes, with major ramifications for evolution and conservation. A recent study found that hybrid tiger salamanders had higher metabolic rates than their parental forms. Specifically, the ratio of resting metabolic rate to water loss, which was used as a measure of performance, was greater in hybrids. Recent genetic research showed that over half of the experimental subjects in that study were genetically pure California tiger salamanders (Ambystoma californiense) misclassified as hybrids. We reanalyzed the data using the corrected identification of hybrids and parentals. As expected, updating the classification revealed even stronger evidence for differences between hybrids and parentals. Hybrids had higher resting metabolic rates and greater water loss than parentals. The ratio of resting metabolic rate to water loss was also higher in hybrids. However, we suggest that this ratio might not be a positive measure of salamander performance. Higher metabolic rate means higher energy expenditure, and higher water loss suggests increased risk of desiccation. Both are major challenges for terrestrial amphibians, especially salamanders, which are hypothesized to be low-energy, low-water-loss specialists. Under this hypothesis, the ratio of energy expenditure to water loss is a ratio of two costs rather than a ratio of benefit to cost. While our analyses corroborate and strengthen the previous statistical results, we suggest that high resting metabolic rate is better interpreted as hybrid dysfunction, not vigor. Here, both hypotheses are speculative, and specific research on the fitness effects of these physiological differences is needed to resolve this important ecological question.

Ambystoma californiense↗
DOE OSTI2025

Evaluation of the Energy, Hygrothermal, and Thermal Capacity Performance of Cross-Laminated Timber

Cross-laminated timber (CLT) construction is gaining momentum in the US because it offers multiple advantages over traditional construction methods. Benefits that have received the most attention focus on constructability, the environment, and protection (e.g., blast resistance), although CLT construction is likely to offer other benefits, as well. Still, these have not been studied at length because such evaluations are costly, requiring long-term assessments in an actual building and specialized technical knowledge. Among the possible benefits, CLT construction likely provides a higher-performing building envelope. Using CLT panels to enclose a building means fewer joints in the opaque envelope than what is required in traditional stick-framed construction. Fewer joints mean fewer locations where the air- and water-resistive barrier (WRB) could be compromised; thus, a CLT building enclosure may require less maintenance and have a longer lifespan than a traditionally built structure because of fewer air and water leaks. In addition, CLT’s thermal mass moderates indoor temperatures, allowing the heating, ventilation, and air conditioning (HVAC) system to operate more efficiently during peak hours, reducing operational energy consumption throughout the lifetime of the CLT building (Salonvaara et al., 2022). Furthermore, more stable indoor temperatures can increase occupant comfort. The CLT’s thermal mass can also reduce energy costs by adjusting to utility time-of-use pricing without affecting occupant comfort. The ability of CLT buildings to bridge periods without HVAC operation prepares them for future grid interaction and provides a certain level of resilience against power outages. Researchers have attempted to quantify these benefits; however, their work is based on simplified simulations with numerous assumptions. To correctly understand the benefits, an actual building must be monitored. Therefore, information needs to be gathered on indoor and outdoor temperatures, HVAC energy consumption, thermostat setpoints, temperatures, and thermal transport in CLT components to comprehend how these parameters are affected by the CLT’s thermal mass. These data are needed to reduce the number of assumptions and calibrate simulation models to optimize HVAC controls to minimize overall energy consumption, reduce energy use and higher fees during peak demand, and maintain occupant comfort. Additionally, the calibrated simulation model allows the optimization exercise to be repeated in various US climates. Potential benefits can be tailored to buildings in various locations, and decisions can be made on where CLT construction could be most advantageous. Furthermore, monitoring and simulation results are needed to evaluate the durability of the CLT structures in different climates. This project’s researchers gathered information to help understand and quantify the benefits of CLT buildings concerning operational energy, moderated indoor temperatures, and comfort; the dynamic operation to provide grid services; and resilience in times of power outage. Through the corroboration of simulation models with real-world measurements, this study paves the way for extrapolating findings to other climatic zones and building typologies, thereby broadening the understanding of CLT’s multifaceted benefits and reinforcing its position as a material of choice in sustainable construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1994

A Redetermination of the Dissociation Energy of MgO(+)

In 1986, we reported a dissociation energy (D(sub 0) of 2.31 eV for the X(sup 2)Pi ground state of MgO(+). This value was determined by computing the dissociation energy to the Mg(2+) + O(-) limit and adjusting the value to the Mg(+) + O limit using the experimental Ionization Potential (IP) of Mg(+) and the Electron Affinity (EA) of O. The success of this method relies on the assumption that there is little covalent contribution to the bonding. The very small (0.04 eV) correlation contribution to the binding energy was taken as corroboration for the validity of this approach. Our earlier theoretical value was estimated to be accurate to at least 0.2 eV. It is in excellent agreement with the subsequent value of 2.30 +/- 0.13 eV determined by Freiser and co-workers from photodissociation experiments. It is also consistent with the upper (less than 3.1 eV) and lower (greater than 1.1 eV) bounds determined by Rowe obtained by studying the reactions of Mg(+) with 03 and NO2. However, it is inconsistent with an upper bound of 1.7 eV reported by Kappes and Staley based on their failure to observe MgO(+) in the reaction of Mg(+) with N2O. The picture became somewhat clouded, however, by the recent guided-ion beam mass spectrometric studies of Dalleska and Armentrout. Their initial analysis of the reaction data for Mg(+) + O2 lead to a bond dissociation energy of 2.92 +/- 0.25 eV, which is considerably larger than the value of 2.47 +/- 0.06 eV deduced from their studies of the Mg(+)+NO2 reaction.

Bauschlicher, Charles W., Jr.↗