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DOE OSTI2023

Nuclear Structure and Decay Data for A=167 Isobars

Experimental nuclear spectroscopic data are compiled and evaluated for 17 known nuclides of mass 167 (Sm, Eu, Gd, Tb, Dy, Ho, Er Tm, Yb, Lu, Hf, Ta, W, Re, Os, Ir, Pt), 23 years after the previous full evaluation by 2000Ba65. Detailed information is presented for each reaction and decay experiment. Combining all the available data, recommended values are provided for energies, spins and parities, and half-lives of levels, with energies, branching ratios and multipolarities of γ radiations, and characteristics of β and α radiations in radioactive decays. Here, the α decays of A=171 nuclei to A=167 daughters are included in this work, while for α decays of A=167 nuclei to A=163 daughters, consult Nuclear Data Sheets (2010Re03) or the ENSDF database for A=163. 167 Er, 167 Tm, 167 Yb, 167 Lu and 167 Ta are among the most extensively studied nuclides via decay and high-spin gamma-ray spectroscopy measurements, followed by 167 Ho, 167 Hf, 167 W, and 167 Os. Information for excited states in 167 Dy, 167 Re, and 167 Ir are limited; no excited states have yet been identified in 167 Sm, 167 Eu, 167 Gd, 167 Tb and 167 Pt, with the ground-state half-life of 167 Sm remaining unknown. This work supersedes the earlier evaluation of A=167 nuclei by 2000Ba65.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1983

Airborne measurements of laser backscatter from the ocean surface

The data are taken with three different pulsed laser sources, one each in the ultraviolet (337.1 nm), visible (532.1 nm) and infrared (9.5 microns). The principal instrument is the airborne oceanographic lidar of the NASA Wallops Flight Facility. The data on mean laser backscatter and its variation with angle off nadir are found to be consistent with previous analytical work and some previous experimental work. The absolute calibration of this backscatter in terms of an effective Lambertian reflectance is less precise, but the data support values near nadir of approximately 0.20 for low wind speeds. It is noted that these values are 1 order of magnitude larger than the Fresnel reflectance for an air/water discontinuity in the refractive index. Whereas the normalized standard deviation (modulation factor) of backscatter is less well understood analytically, it is defined by these measurements to range from a few percent to over 50 percent at nadir and to increase off nadir as the tangent of theta or faster. The data are uncertain beyond 15 deg off nadir owing to a dynamic range limitation.

Bufton, J. L.↗

DOE OSTI2016

Bringing Fenton Hill into the Digital Age: Data Conversion in Support of the Geothermal Technologies Office Code Comparison Study Challenge Problems

The Geothermal Technologies Office Code Comparison Study (GTO-CCS) was established by the U.S. Department of Energy to facilitate collaboration among members of the geothermal modeling community and to evaluate and improve upon the ability of existing codes to simulate thermal, hydrological, mechanical, and chemical processes associated with complex enhanced geothermal systems (EGS). The first stage of the project, which has been completed, involved comparing simulations for seven benchmark problems that were primarily designed using well-prescribed, simplified data sets. In the second stage, the participating teams are tackling two challenge problems based on the EGS research conducted in hot dry rock (HDR) at Fenton Hill, near Los Alamos, New Mexico. The Fenton Hill project, conducted by Los Alamos National Laboratory (LANL) from 1970 to 1995, was the world’s first HDR demonstration project. One of the criteria for selecting this experiment as the basis for the challenge problems was the amount and availability of data for generating model inputs. The Fenton Hill HDR system consisted of two reservoirs – an earlier Phase I reservoir tested from 1974 to 1981 and a deeper Phase II reservoir tested from 1980 to 1995. Detailed accounts of both phases of the HDR project have been presented in a number of books and reports, including a recently published summary of the lessons learned and a final report with a chronological description of the Fenton Hill project, prepared by LANL. Project documents and records have been archived and made public through the National Geothermal Data System (NGDS). Some of the data acquired from Phase II are available in electronic format readable on modern computers. These include the microseismic data from some of the important experiments (e.g. the massive hydraulic fracturing test conducted in 1983) and the injection/production wellhead data from the circulation tests conducted between 1992-1995. However, much of the data collected during the project, while publicly available, currently only exist in the form of tables or graphs within scanned documents. Therefore, in support of the GTO-CCS, the data needed for developing simulation inputs are being compiled and converted to platform independent, open readable formats so that all participating teams will have access to the same electronic data set. In some cases this requires conversion using optical character recognition, digitizing existing images, and generating the appropriate metadata from project documents. The GTO-Velo knowledge management framework, developed by Pacific Northwest National Laboratory (PNNL), was used for the benchmark problem stage of the comparison study and will also be used as the data repository for the challenge problem data sets. It is staggering and impractical to convert all published data for the Fenton Hill site, so the focus is on data that supports simulations for the three topical areas defined by the study for the challenge problems: 1) reservoir creation/stimulation, 2) reactive and passive transport, and 3) thermal recovery. Conversion of these data provide value not only to GTO-CCS participants, but also to members of the geothermal community at large who may be interested in revisiting the Fenton Hill experiment in the future.

Code Comparison Study↗

DOE OSTI2014

Social vulnerability indicators as a sustainable planning tool

In the face of global warming and environmental change, the conventional strategy of resource centralization will not be able to cope with a future of increasingly extreme climate events and related disasters. It may even contribute to inter-regional disparities as a result of these events. To promote sustainable development, this study offers a case study of developmental planning in Chiayi, Taiwan and a review of the relevant literature to propose a framework of social vulnerability indicators at the township level. The proposed framework can not only be used to measure the social vulnerability of individual townships in Chiayi, but also be used to capture the spatial developmental of Chiayi. Seventeen social vulnerability indicators provide information in five dimensions. Owing to limited access to relevant data, the values of only 13 indicators were calculated. By simply summarizing indicators without using weightings and by using zero-mean normalization to standardize the indicators, this study calculates social vulnerability scores for each township. To make social vulnerability indicators more useful, this study performs an overlay analysis of social vulnerability and patterns of risk associated with national disasters. The social vulnerability analysis draws on secondary data for 2012 from Taiwan's National Geographic Information System. The second layer of analysis consists of the flood potential ratings of the Taiwan Water Resources Agency as an index of biophysical vulnerability. The third layer consists of township-level administrative boundaries. Analytical results reveal that four out of the 18 townships in Chiayi not only are vulnerable to large-scale flooding during serious flood events, but also have the highest degree of social vulnerability. Administrative boundaries, on which social vulnerability is based, do not correspond precisely to “cross-administrative boundaries,” which are characteristics of the natural environment. This study adopts an exploratory approach that provides Chiayi and other government agencies with a foundation for sustainable strategic planning for environmental change. The final section offers four suggestions concerning the implications of social vulnerability for local development planning. -- Highlights: • This study proposes a framework of social vulnerability indicators at the township level in Chiayi County, Taiwan. • Seventeen social vulnerability indicators are categorized into four dimensions. • This study performs a three-layer overlay analysis of social vulnerability and natural disaster risk patterns. • 4 out of the 18 townships not only have potential for large-scale flooding, but also high degree of social vulnerability. • This study provides a foundation for sustainable strategic planning to deal with environmental change. • Four suggestions are proposed regarding the implications of social vulnerability for local development planning.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2008

Delay-Throughput Performance of the Deep-Space Ka-band Link

In this paper, performance of a first-in, first-out (FIFO), selective retransmission scheme for the deep-space Ka-band link is presented and compared to the performance of a comparable X-band link. In this analysis, 16 months of water vapor radiometer (WVR) and advanced water vapor radiometer (AWVR) data from the three Deep Space Network (DSN) Communication Complexes (DSCC) were used to emulate weather effects on X-band and Ka-band links from Mars. Mars Reconnaissance Orbiter (MRO) X-band and Ka-band telecommunications parameters were used for spacecraft telecommunications capabilities. One pass per week per complex was selected from MRO's Deep Space Network (DSN) schedule from April 1, 2006 to August 31, 2007 for a total of 207 passes (69 passes per complex) for this analysis. For each pass both X-band and Ka-band links were designed using at most two data rates so that the expected pass capacity would be maximized subject to a minimum availability requirement (MAR). In conjunction with the WVR/AWVR data, elevation profiles of the selected passes and models for the performance of the antennas in the DSN were used to emulate the performance of both links. It was assumed that the retransmission of the data takes place not on the same pass as the original transmission but during subsequent passes. The data collected before a pass was assumed to be a fraction of the expected capacity of the pass as calculated through the link design process. Infinite spacecraft storage was assumed to obtain an upper bound on the spacecraft storage requirement. The independent parameters of this analysis were MAR and the ratio of data collected before a pass to the expected pass capacity. Since the selected passes did not occur at regular intervals, the delay in this analysis was measured in terms of number of passes. The throughput was measured in terms of number of bits received successfully on the ground. The results indicate that reasonable delay performance could be achieved with very high throughput for relatively low MAR values for data collection to expected pass capacity ratio of around 97% for Ka-band. The results indicate that, except for very low average delay requirements, the Ka-band link provides more than twice the throughput of the X-band link for the same amount of power consumed by the spacecraft. In addition, the results indicate that the required storage onboard the spacecraft is not prohibitive and good performance could be achieved by using a buffer size less than three times the maximum amount of data collected before a pass.

Shambayati, Shervin↗

NASA NTRS2008

Delay-Throughput Performance the Deep-Space Ka-Band Link

Shambayati, Shervin↗

NASA NTRS2024

Extending the Utility of Space-Borne Snow Water Equivalent Observations Over Vegetated Areas With Data Assimilation

Snow is a vital component of the earth system, yet no snow-focused satellite remote sensing platform currently exists. In this study, we investigate how synthetic observations of snow water equivalent (SWE) representative of a synthetic aperture radar remote sensing platform could improve spatiotemporal estimates of snowpack. We use a fraternal twin observing system simulation experiment, specifically investigating how much snow simulated using widely used models and forcing data could be improved by assimilating synthetic observations of SWE. We focus this study across a 24° x 37° domain in the western USA and Canada, simulating snow at 250 m resolution and hourly time steps in water year 2019. We perform two data assimilation experiments, including (1) a simulation excluding synthetic observations in forests where canopies obstruct remote sensing retrievals and (2) a simulation inferring snow distribution in forested grid cells using synthetic observations from nearby canopy-free grid cells. Results found that, relative to a nature run, or assumed true simulation of snow evolution, assimilating synthetic SWE observations improved average SWE biases at maximum snowpack timing in shrub, grass, crop, bare-ground, and wetland land cover types from 14 %, to within 1 %. However, forested grid cells contained a disproportionate amount of SWE volume. In forests, SWE mean absolute errors at the time of maximum snow volume were 111 mm and average SWE biases were on the order of 150 %. Here the data assimilation approach that estimated forest SWE using observations from the nearest canopy-free grid cells substantially improved these SWE biases (18 %) and the SWE mean absolute error (27 mm). Simulations employing data assimilation also improved estimates of the temporal evolution of both SWE and runoff, even in spring snowmelt periods when melting snow and high snow liquid water content prevented synthetic SWE retrievals. In fact, in the Upper Colorado River region, melt-season SWE biases were improved from 63 % to within 1 %, and the Nash–Sutcliffe efficiency of runoff improved from −2.59 to 0.22. These results demonstrate the value of data assimilation and a snow-focused globally relevant remote sensing platform for improving the characterization of SWE and associated water availability.

Justin Pflug↗

DOE OSTI2024

Nuclear Structure and Decay Data for A=165 Isobars

Experimental nuclear spectroscopic data are compiled and evaluated for 18 known nuclides of mass 165 (Pm, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Hf, Ta, W, Re, Os, Ir, Pt). Detailed information is presented for each reaction and decay experiment. Combining all the available data, recommended values are provided for energies, spins and parities, and half-lives of levels, with energies, branching ratios and multipolarities of γ radiations, and characteristics of β and α radiations in radioactive decays. 165 Dy, 165 Ho, 165 Er, 165 Tm, 165 Yb, 165 Lu and 165 Hf are among the most extensively studied nuclides via decay and high-spin gamma-ray spectroscopy measurements, followed by limited data for 165 Tb, 165 Ta, 165 W, 165 Re, and 165 Os. No excited states have yet been identified in 165 Sm, 165 Gd, and 165 Pt, while for 165 Eu and 165 Ir, information is available for only the g.s. and an isomer, but with no γ rays. As a result, this work supersedes earlier evaluation of A=165 nuclides by 2006Ja09.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1973

Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation

The author has identified the following significant results. The Great Plains Corridor rangeland project utilizes natural vegetation systems as phenological indicators of seasonal development and climatic effects upon regional growth conditions. A method has been developed for quantitative measurement of vegetation conditions over broad regions using ERTS-1 MSS data. Radiance values recorded in ERTS-1 spectral bands 5 and 7, corrected for sun angle, are used to compute a band ratio parameter which is shown to be correlated with green biomass and vegetation moisture content. This report details the progress being made toward determining factors associated with the transformed vegetation index (TVI) and limitations on the method. During the first year of ERTS-1 operation (cycles 1-20), an average of 50% usable ERTS-1 data was obtained for the ten Great Plains Corridor test sites.

Rouse, J. W., Jr.↗

DOE OSTI2026

Processed sap flow and fine-root trait data associated with summer drought responses in temperate trees in Lisle, Illinois, USA (2019–2021)

These data support the manuscript “Acquisitive root exploration strategies help maintain higher peak sap flux rates during summer drought, but more root biomass does not”. The dataset includes processed sap flow measurements and fine-root trait data collected between 2019 and 2021 from temperate monodominant tree plots established in the 1920s to 1930s ranging in size from 0.05 to 0.8 ha at The Morton Arboretum in Lisle, IL. Sap flow was measured with ICT sap flow sensors using the heat ratio method. Fine-root traits were measured from soil cores which includes specific root length (SRL), specific root area (SRA), diameter, biomass, and length for diameter classes ≤1 mm and ≤2 mm. The package contains comma separated value (CSV) data files and associated metadata that can be viewed and analyzed using common software such as spreadsheet programs, R, and Python. These data are used to investigate how variation in fine-root traits relate to tree water use and drought response during summer drought linking belowground root traits and aboveground physiological responses.

drought↗

NASA NTRS2005

Intelligent systems in space : the EO-1 Autonomous Sciencecraft

The Autonomous Sciencecraft Software (ASE) is currently flying onboard the Earth Observing One (EO-1) Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and runtime robust execution. Because of the deployment to the EO-1 spacecraft, the ASE software has stringent constraints of autonomy and limited computing resources. We describe these constraints and how they are reflected in our operations approach. A summary of the final results of the experiment is also included. This software has demonstrated the potential for space missions to use onboard decision-making to detect, analyze, and respond to science events, and to downlink only the highest value science data. As a result, ground-based mission planning and analysis functions have been greatly simplified, thus reducing operations cost.

Earth Observing One (EO-1) Spacecraft↗

NASA NTRSDate not supplied

Machine Learning based Aircraft Performance Model Estimation for Trajectory Prediction

The accurate prediction of aircraft trajectory by ground-based decision support tools is a critical component of air traffic management in the US National Airspace System (NAS). Accurate predictions of where the aircraft will be in the future or when they will arrive at specific locations (e.g., fixes) is a key enabler for sequencing and efficient arrival management of flights. Traditional physics based aircraft trajectory prediction relies on a simplified point-mass total energy model whose parameters are referred to as Aircraft Performance Model (APM) parameters. Even though the performance coefficients and weight of an aircraft are a vital part of the aircraft performance model’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to decision-support tools. Current approaches freeze some coefficients to default base of aircraft data (BADA) values and optimize others. However, the APM parameters are highly coupled by the flight dynamics and prioritizing one parameter over others leads to bias and skewed predictions. To alleviate this problem, we provide a combined optimization framework to predict all the critical (thrust, drag and weight) APM parameters. This paper is focused on training Machine Learning (ML) models that map historical flights to optimized APM parameters that provide the best fit (in terms of prediction error). Our dataset obtained from NASA’s Sherlock data warehouse is comprised of thousands of historical flights and includes weather and track data collected from 2019. Using different subsets of relevant features (e.g., aircraft type), we trained several ML models to estimate the aircraft’s take off weight, drag polar coefficients (both parasitic and lift induced), and thrust settings (multiplier applied to the maximum engine thrust). The chosen flights are from three of the most common aircraft types (B738, B737, and A320) arriving at four airports (LAX, DEN, MSP, and DFW). Our ML approach is comprised of two different solutions: 1- using a subset of features that are known prior to the flight departure and do not change during flight (such as engine type, current temperature at departure & destination airports, aircraft type) and 2 - using a subset of temporal features of the flight trajectory (such as cruise altitude, Mach, airspeed, and rate of climb) in addition to the pre-departure features from the first solution. The labels or target variables are the APM parameters that were obtained by an optimized ordinary differential equations (ODE) fitting process (applied to individual flights). The ODE-fitting is very time intensive and is therefore performed offline. Thus, training an ML model to learn the relationship between the flight features and ODE-generated labels enables faster estimation of the APM parameters and is therefore amenable to real-time prediction. Various ML models including linear regression, random forest, XGBoost, and neural network were trained, and the results are compared. After model validation and hyperparameter-tuning, we observed that the Random Forest model outperformed the other three models by the overall mean square error (MSE) of 2% for the first solution and 1.5% for the second solution. Finally, the ML-derived parameters are compared against default BADA APM parameters using NASA’s Autonomy Development toolkit (ADK) simulation software. The simulation results for one of each aircraft type is shown and discussed.

Aida Sharif Rohani↗

NASA NTRS2023

Data Sharing in Radiation Biology: Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally "Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗

DOE OSTI2011

Development of 5- and 10-year-old pediatric phantoms based on polygon mesh surfaces

Purpose: The purpose of this study is the development of reference pediatric phantoms for 5- and 10-year-old children to be used for the calculation of organ and tissue equivalent doses in radiation protection. Methods: The study proposes a method for developing anatomically highly sophisticated pediatric phantoms without using medical images. The 5- and 10-year-old male and female phantoms presented here were developed using 3D modeling software applied to anatomical information taken from atlases and textbooks. The method uses polygon mesh surfaces to model body contours, the shape of organs as well as their positions, and orientations in the human body. Organ and tissue masses comply with the corresponding data given by the International Commission on Radiological Protection (ICRP) for the 5- and 10-year-old reference children. Bones were segmented into cortical bone, spongiosa, medullary marrow, and cartilage to allow for the use of micro computer tomographic ({mu}CT) images of trabecular bone for skeletal dosimetry. Results: The four phantoms, a male and a female for each age, and their organs are presented in 3D images and their organ and tissue masses in tables which show the compliance of the ICRP reference values. Dosimetric data, calculated for the reference pediatric phantoms by Monte Carlo methods were compared with corresponding data from adult mesh phantoms and pediatric stylized phantoms. The comparisons show reasonable agreement if the anatomical differences between the phantoms are properly taken into account. Conclusions: Pediatric phantoms were developed without using medical images of patients or volunteers for the first time. The models are reference phantoms, suitable for regulatory dosimetry, however, the 3D modeling method can also be applied to medical images to develop patient-specific phantoms.

61 RADIATION PROTECTION AND DOSIMETRY↗

NASA NTRS1982

Investigation of Antarctic crust and upper mantle using MAGSAT and other geophysical data

Antarctica is the perfect proving ground for testing data reduction procedures which are alternatives to the standard procedure employing polynomial fitting. Unreduced data (observed values minus corefield model theo each pass) were averaged in 3 degree bins. The resulting map was then high pass filtered using a finite Fourier transform filter so that spectral peaks between 4200 km and 5280 km were diminished by 1/3, peaks corresponding to wavelengths greater than or equal to 5280 km were diminished by 1/2, and the d.c. component was set equal to zero. The surface subtracted in this way differs from the polynomials used in the standard method in that it is static over the 5 north data window. The map produced is presented and the effects of the static model are compared to those of the dynamic mode.

Bentley, C. R.↗

NASA NTRS2011

Visible and Near-IR Reflectance Spectra of Smectite Acquired Under Dry Conditions for Interpretation of Martian Surface Mineralogy

Visible and near-IR (VNIR) spectra from the MEx OMEGA and the MRO CRISM hyper-spectral imaging instruments have spectral features associated with the H2O molecule and M OH functional groups (M = Mg, Fe, Al, and Si). Mineralogical assignments of martian spectral features are made on the basis of laboratory VNIR spectra, which were often acquired under ambient (humid) conditions. Smectites like nontronite, saponite, and montmorillionite have interlayer H2O that is exchangeable with their environment, and we have acquired smectite reflectance spectra under dry environmental conditions for interpretation of martian surface mineralogy. We also obtained chemical, Moessbauer (MB), powder X-ray diffraction (XRD), and thermogravimetric (TG) data to understand variations in spectral properties. VNIR spectra were recorded in humid lab air at 25-35C, in a dynamic dry N2 atmosphere (50-150 ppmv H2O) after exposing the smectite samples (5 nontronites, 3 montmorillionites, and 1 saponite) to that atmosphere for up to approximately l000 hr each at 25-35C, approximately 105C, and approximately 215C, and after re-exposure to humid lab air. Heating at 105C and 215C for approximately 1000 hr is taken as a surrogate for geologic time scales at lower temperatures. Upon exposure to dry N2, the position and intensity of spectral features associated with M-OH were relatively insensitive to the dry environment, and the spectral features associated with H2O (e.g., approximately 1.90 micrometers) decreased in intensity and are sometimes not detectable by the end of the 215C heating step. The position and intensity of H2O spectral features recovered upon re-exposure to lab air. XRD data show interlayer collapse for the nontronites and Namontmorillionites, with the interlayer remaining collapsed for the latter after re-exposure to lab air. The interlayer did not collapse for the saponite and Ca-montmorillionite. TG data show that the concentration of H2O derived from structural OH was invariant to the dry N2 treatment for saponite and the montmorillionites, but the nontronites had additional structural OH after treatment. Upon exposure to dry N2, the VNIR spectra also acquired a red slope with decreasing albedo between approximately 0.4 and approximately 2.0 micrometers. The magnitude of the effects covaries with exposure time to dry N2 and heating temperature. Upon re-exposure to lab air, the slope and albedo do not completely recover to pre-exposure values. MB data show that these effects do not result from partial reduction of ferric to ferrous iron, and TG data show they do not result from loss of structural OH. Possible explanations include formation of small clusters of (superparamagnetic) ferric oxide and reduced smectite crystallinity. The difference in spectral properties between spectra acquired in humid lab air and under dry conditions are consequential for interpretation of CRISM and OMEGA spectra. For example, nontronite by itself and not nontronite plus ferrihydrite can account for the red spectral slope in martian spectra where nontronite is indicated by the Fe-OH spectral features.

Morris, Richard V.↗

DOE OSTI2026

Redefining fuel heating value for engines: Accounting for heat of vaporization

Defining a fuel's heating value (i.e., energy content) is fundamental for calculating engine efficiency and for life cycle analysis comparisons between different fuels. Traditional definitions of lower heating value and higher heating value account for the effect of water vapor versus liquid water in the exhaust, which is important when the fuel is used in a furnace or boiler. In an engine, it is equally important to properly account for the energy required to vaporize liquid fuel. Heat of vaporization has a small effect for common hydrocarbon fuels, typically less than 1% of lower heating value, but the effect is much larger for other important fuels such as ethanol (3.4% of lower heating value) and methanol (5.9% of lower heating value). This paper defines a new type of fuel heating value that more accurately reflects the useful fuel energy content for engines. Vaporized heating value is defined as the heating value when starting with a vaporized fuel instead of a liquid fuel. It can be calculated by adding the fuel's heat of vaporization to the traditional lower heating value. This paper illustrates the rationale and benefits of using vaporized heating value using data from the literature.

09 BIOMASS FUELS↗

NASA NTRS1977

Optimum performance of suppressed carrier receivers with Costas loop tracking

The performance of suppressed carrier receivers with Costas loop tracking is optimized by proper choice of loop arm filter bandwidth. In particular, it is shown that for a variety of passive arm filter types, there exists, for a given data rate and data signal-to-noise ratio, an optimum filter bandwidth in the sense of minimizing the loop's squaring loss. For the linear theory case, this is equivalent to minimizing the loop's tracking jitter. When symbol synchronization is known, it is shown that by replacing the passive arm filters with active filters, i.e., integrate-and-dump circuits, one can achieve an improvement in carrier-to-noise ratio of as much as 4 to 6 dB depending on the passive arm filter type used for comparison and the value of data signal-to-noise ratio.

Simon, M. K.↗