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Method for estimating critical molar volume of materials is faster and simpler than previous procedures. Formula sums no more than 18 different contributions from components of chemical structure of material, and is as accurate (within 3 percent) as older more complicated models. Method should expedite many thermodynamic design calculations.
Accurate timber inventory data for cost-effective forest management is the primary goal of a Forest Classification and Inventory System (FOCIS) designed to provide estimates of timber volume by species aggregated by compartments, townships, or other spatial management units. FOCIS uses Landsat spectral data, including a synthesized texture channel, and Forest Service ground sample data to produce timber volume-homogeneous classes through a two-step unsupervised clustering process. Registered digital terrain data, including derived slope angle and slope aspect channels, are used to predict species proportions through a trend surface model, again using ground sample data for model calibration. In the final stage of FOCIS, volume estimates and predicted species proportions are merged and aggregated to yield timber volumes by species within management areas.
The mathematical developments and their computer program implementation for the Space Shuttle propulsion parameter estimation project are summarized. The estimation approach chosen is the extended Kalman filtering with a modified Bryson-Frazier smoother. Its use here is motivated by the objective of obtaining better estimates than those available from filtering and to eliminate the lag associated with filtering. The estimation technique uses as the dynamical process the six degree equations-of-motion resulting in twelve state vector elements. In addition to these are mass and solid propellant burn depth as the ""system'' state elements. The ""parameter'' state elements can include aerodynamic coefficient, inertia, center-of-gravity, atmospheric wind, etc. deviations from referenced values. Propulsion parameter state elements have been included not as options just discussed but as the main parameter states to be estimated. The mathematical developments were completed for all these parameters. Since the systems dynamics and measurement processes are non-linear functions of the states, the mathematical developments are taken up almost entirely by the linearization of these equations as required by the estimation algorithms.
This project, funded by the U.S. Department of Energy – National Energy Technology Laboratory (DOE-NETL) under award DE-FE0032212, evaluated how legacy coal mine lands and coal refuse piles in Central Appalachia (West Virginia and Pennsylvania) can be reclaimed and repurposed to support biomass development and beneficial utilization of waste coal, with the long-term goal of supporting net-zero or net-negative greenhouse gas (GHG) pathways. The project had two primary objectives: 1. Characterize legacy mine sites (including site conditions, waste coal/refuse resources, and soil/ecosystem indicators) and develop reclamation and best management practices (BMPs) for biomass cultivation; and 2. Conduct integrated machine learning (ML)-assisted life cycle assessment (LCA) and techno-economic analysis (TEA) to quantify environmental and economic outcomes for multiple biomass and waste-coal utilization pathways. Across West Virginia, the team identified ~625 coal refuse sites covering ~19,705 acres, and developed methods to estimate refuse pile volume using digital elevation models (DEMs) and geospatial workflows. A large subset of sites received volume estimates totaling ~1.6 billion m³.
OBJECTIVE: A new computerized semi-automatic method for left ventricular (LV) chamber segmentation is presented. METHODS: The LV is imaged by real-time three-dimensional echocardiography (RT3DE). The surface detection model, based on level set techniques, is applied to RT3DE data for image analysis. The modified level set partial differential equation we use is solved by applying numerical methods for conservation laws. The initial conditions are manually established on some slices of the entire volume. The solution obtained for each slice is a contour line corresponding with the boundary between LV cavity and LV endocardium. RESULTS: The mathematical model has been applied to sequences of frames of human hearts (volume range: 34-109 ml) imaged by 2D and reconstructed off-line and RT3DE data. Volume estimation obtained by this new semi-automatic method shows an excellent correlation with those obtained by manual tracing (r = 0.992). Dynamic change of LV volume during the cardiac cycle is also obtained. CONCLUSION: The volume estimation method is accurate; edge based segmentation, image completion and volume reconstruction can be accomplished. The visualization technique also allows to navigate into the reconstructed volume and to display any section of the volume.
Agricultural crop classification models using two or more spectral regions (visible through microwave) were developed and tested and biomass was estimated by including microwave with visible and infrared data. The study was conducted at Guymon, Oklahoma and Dalhart, Texas utilizing aircraft multispectral data and ground truth soil moisture and biomass information. Results indicate that inclusion of C, L, and P band active microwave data from look angles greater than 35 deg from nadir with visible and infrared data improved crop discrimination and biomass estimates compared to results using only visible and infrared data. The active microwave frequencies were sensitive to different biomass levels. In addition, two indices, one using only active microwave data and the other using data from the middle and near infrared bands, were well correlated to total biomass.
Volcanic plains and constructs comprise over half the surface of Mars. Volume estimates require sensible estimates of the thickness of volcanic materials. The completion of the 1:2 M Viking photomosaics and a refined geologic map based on Viking photography set the stage for improved thickness studies and volume estimates. Currently, a revised (but incomplete) data base of 740 partially buried craters was compiled using Mars photomosaics at 1:2 M for initial identification and measurement.
Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.
Subroutines, logic, and input/output formats for STEP programs on preflight and postflight trajectory measurement
The author has identified the following significant results. A unique digital timber volume estimation system was developed for use with the MSS CCT tapes. The system was tested on a 64-square mile area in Northern California's Trinity Alps. The outcome of a systematic experiment, in which several possible combinations of bands 5 and 7 and a contrast measure were tried, showed that an estimated gain in precision of 50% can be obtained in a multistage sampling design. The difference between bands 5 and 7 proved to be of special importance for the estimation of biomass in the form of timber volume. In addition, an interpretation model for high flight U2 photographs was developed. A maximum multiple correlation coefficient of 0.74 was obtained for the regression model, explaining 55% of the variation in timber volume as estimated from aerial photos and ground measurments. An interpretation model for MSS color composites is in the testing stage.
Orthostatic intolerance affects 60‐80% of astronauts returning from long‐duration missions, representing a significant risk to completing mission‐critical tasks. While likely multifactorial, a reduction in stroke volume (SV) represents one factor contributing to orthostatic intolerance during stand and head up tilt (HUT) tests. Current measures of SV during stand or HUT tests use Doppler ultrasound and require a trained operator and specialized equipment, restricting its use in the field. BeatScope (Finapres Medical Systems BV, The Netherlands) uses a modelflow algorithm to estimate SV from continuous blood pressure waveforms in supine subjects; however, evidence supporting the use of Modelflow to estimate SV in subjects completing stand or HUT tests remain scarce. Furthermore, because the blood pressure device is held extended at heart level during HUT tests, but allowed to rest at the side during stand tests, changes in the finger arterial pressure waveform resulting from arm positioning could alter modelflow estimated SV. The purpose of this project was to compare Doppler ultrasound and BeatScope estimations of SV to determine if BeatScope can be used during stand or HUT tests. Finger photoplethysmography was used to acquire arterial pressure waveforms corrected for hydrostatic finger‐to‐heart height using the Finometer (FM) and Portapres (PP) arterial pressure devices in 10 subjects (5 men and 5 women) during a stand test while simultaneous estimates of SV were collected using Doppler ultrasound. Measures were made after 5 minutes of supine rest and while subjects stood for 5 minutes. Next, SV estimates were reacquired while each arm was independently raised to heart level, a position similar to tilt testing. Supine SV estimates were not significantly different between all three devices (FM: 68+/-20, PP: 71+/-21, US: 73+/-21 ml/beat). Upon standing, the change in SV estimated by FM (‐18+/-8 ml) was not different from PP (‐21+/-12), but both were significantly less than US (‐37+/-16 ml, p<.05). Raising finger BP devices to heart level caused no significant change in SV measured with any of the devices (FM: 1.5+/-19, PP: 1.7+/-26, US: 0.5+/-6), although variability was 3‐6x greater as assessed by both blood pressure devices compared to US. Retrospective analysis of blood pressure data to assess SV in 11 supine subjects revealed significantly different estimates between methods (FM: 95+/-17, US: 75+/-32, p<.05), but the change in SV resulting from HUT was similar between methods (FM: ‐37+/-9, US: ‐40+/-18 ml). However, the correlation coefficient determined from pairs of SV estimated by US and FM was weak (r2=0.03). These data suggest Modelflow cannot be used in lieu of Doppler ultrasound to estimate SV during stand or HUT tests. Further investigation should focus on identifying factors contributing to differences between these measurement techniques in order to make use of a simple method for assessing beat‐by‐beat changes in SV during postural changes, especially during field testing.
There are a variety of constructional volcanic features in Tharsis. These features range from Olympus Mons and the Tharsis Montes shields, to the small low shields and fissure eruptions that characterize much of the volcanic plains, to the smaller volcanic constructs in the northeast and western parts of Tharsis. I describe the geology of the western group, which includes Biblis Patera, Ulysses Patera, and Jovis Tholus. Each of these volcanoes has had a unique, and complex geologic history. Biblis Patera is located at 2.3 deg. N, 123.8 deg. The volcano is elongate in a northwesterly direction and has a large, faulted caldera complex. The flanks of the volcano and adjacent plains are characterized by lava flows, northwest-trending graben and troughs, and caldera-concentric graben and troughs. Biblis Patera is approximately 66 x 127 km with an oval 51 x 56 km caldera; the summit elevation is approximately 2 km above the surrounding plains. The constrcut has an estimated volume of 8-22 x 10(exp 3) cu km. Ulysses Patera is located at 2.7 deg. N, 121.3 deg. W and stands approx. 2-3 km above the surrounding plain; flank slopes are approximately 7 deg. to 12 deg. The caldera floor is quite deep, lying 1.8 to 2.2 km below the caldera rim. The caldera has a void volume of approximately 5000 cu km, the total solid mass volume of the volcano is 7-16 x 10(exp 3) cu km. Jovis Tholus is centered at 18.3 deg N; 117.5 deg W; it is a low relief, volcano with gentle flank slopes of between 3 and 8 deg. The construct is dominated by a series of inset calderas which make up the largest fraction of the area. The caldera complex is offset to the southwest side. Total shield dimensions are approximately 77 km (e-wt) by 62 km (n-s); the caldera complex is approximately 44 x 34 km. The shield is embayed on all sides by younger Amazonian age volcanics. Total relief, relative to the surrounding plains, is probably approximately 2 km. The total volume of Jovis Tholus is estimated to be approximately 2-5 x 10(exp 3) cu km.
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The basaltic fill of Oceanus Procellarum has been formally subdivided into four lithostratigraphic formations: The Repsold Formation, the Telemann Formation, the Hermann Formation, and the Sharp Formation. The Repsold Formation is composed of high-Ti basalts and pyroclastic deposits with an estimated age of 3.75 + or - 0.05 b.y. and an estimated volume of about 2.1 x 10 to the 5th cu km. This is overlain by the Telemann Formation composed of very low-Ti basalts and pyroclastic deposits with an estimated age of 3.6 + or - 0.2 b.y. and a volume of 4.2 x 10 to the 5th cu km. The Hermann Formation, composed of intermediate basalts with an estimated age of 3.3 + or - 0.3 b.y., represents the next youngest unit with an estimated volume of 2.2 x 10 to the 5th cu km. The youngest materials in Procellarum are the medium-to-high-Ti basalts comprising the Sharp Formation with an estimated age of 2.7 + or - 0.7 b.y. and a volume of 1.8 x 10 to the 4th cu km.
Real-time highly resolved spatial-temporal vehicle energy consumption is a key missing dimension in transportation data. Most roadway link-level vehicle energy consumption data are estimated using average annual daily traffic measures derived from the Highway Performance Monitoring System; however, this method does not reflect day-to-day energy consumption fluctuations. As transportation planners and operators are becoming more environmentally attentive, they need accurate real-time link-level vehicle energy consumption data to assess energy and emissions; to incentivize energy-efficient routing; and to estimate energy impact caused by congestion, major events, and severe weather. This paper presents a computational workflow to automate the estimation of time-resolved vehicle energy consumption for each link in a road network of interest using vehicle probe speed and count data in conjunction with machine learning methods in real time. The real-time pipeline can deliver energy estimates within a couple seconds on query to its interface. The proposed method was evaluated on the transportation network of the metropolitan area of Chattanooga, Tennessee. The volume estimation results were validated with ground truth traffic volume data collected in the field. To demonstrate the effectiveness of the proposed method, the energy consumption pipeline was applied to real-world data to quantify road transportation-related energy reduction because of mitigation policies to slow the spread of COVID-19 and to measure energy loss resulting from congestion.
Acoustical system proposed to measure depth of a "blind" shaft. Acoustic wave guided by shaft and provides estimate of shaft length, from which volume estimated. Acoustic-generator system determines resonant-frequency difference to measure shaft length.
NREL provided technical assistance for the I-95 Corridor Coalition to develop traffic volume estimates based upon third party probe vehicle data and other sources. The overall objective to accelerate the timeframe for achieving viable estimates was achieved.
The author has identified the following significant results. A unique digital timber volume estimation system with digital data for two ERTS-1 MSS bands was tested. The system was tested on a 64-square mile area in Northern California's Trinity Alps. The outcome of a systematic experiment in which possible combinations of the two bands (MSS 5 and 7) were tried, showed than an estimated gain in precision of 50% can be obtained in a multistage sampling design. Especially the difference between the two bands proved to be of major importance for the estimation of biomass in the form of timber volume. Identical tests as the one performed will be conducted with various S-192 bands when the digital data become available.