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The Strategic Petroleum (SPR) is the world’s largest supply of crude oil. The reserve consists of fours sites in Louisiana and Texas. Each site stores crude in deep, underground salt caverns. It is the mission of the SPR’s Enhanced Monitoring Program to examine all available data to inform our understanding of each site. This report discusses the data, processes and results for each of the four sites.
ECORP Consulting, Inc. conducted a nocturnal small mammal trapping survey within Lawrence Livermore National Laboratory’s (LLNL) Site 300 and the adjacent California Department of Fish and Wildlife (CDFW) Corral Hollow Ecological Reserve. Both sites are located east of the City of Livermore and southwest of the City of Tracy, Alameda and San Joaquin Counties, California (Figure 1-1). A small mammal trapping survey of the project site was conducted in 2002 in preparation for the 2005 LLNL Site-Wide Environmental Impact Statement (SWEIS; Jones & Stokes 2003). The San Joaquin pocket mouse (Perognathus inornatus) was the only special-status species (federal species of concern) captured on Site 300 during the study (West and Woollett 2003). However, since then P. inornatus was taxonomically split into separate subspecies and the pocket mouse species identified on Site 300 in 2002 is no longer considered a special-status species. The 2002 survey also captured woodrats, but identification of the subspecies was not possible. Further investigation was necessary to determine if the woodrat species on the project site was the federally listed (endangered) riparian (San Joaquin Valley) woodrat (Neotoma macrotis riparia [Formerly described as Neotoma fuscipes riparia]), the common Diablo Range woodrat (N. f. perplexa), or another form.
Monitoring cavern leaching after each calendar year of oil sales is necessary to support cavern stability efforts and long-term availability for oil drawdowns in the U.S. Strategic Petroleum Reserve. Modeling results from the SANSMIC code and recent sonars are compared to show projected changes in the cavern’s geometry due to leaching from raw-water injections. This report aims to give background on the importance of monitoring cavern leaching and provide a detailed explanation of the process used to create the leaching plots used to monitor cavern leaching. In the past, generating leaching plots for each cavern in a given leaching year was done manually, and every cavern had to be processed individually. A Python script, compatible with Earth Volumetric Studio, was created to automate most of the process. The script makes a total of 26 plots per cavern to show leaching history, axisymmetric representation of leaching, and SANSMIC modeling of future leaching. The current run time for the script is one hour, replacing 40-50 hours of the monitoring cavern leaching process.
This project will study the feasibility and identify the preferred options necessary to allow the Pechanga Tribal Utility, now renamed Pechanga Western Electric (“PWE”) to carefully and thoughtfully expand from providing electrical service to the Tribe’s commercial enterprises and government center loads to also providing electrical service to the Tribe’s over 300 residential loads and potential future non-tribal commercial loads on the reservation. As well as, explore an option under which PWE will acquire solar and battery storage systems for the residential community.
The U.S. Strategic Petroleum Reserve (SPR) is a crude oil storage system administered by the U.S. Department of Energy. SPR injected a total of over 230 MMB of raw water into 48 caverns as part of oil sales in CY22. Leaching effects were monitored in these caverns to understand how the sales operations may impact the long-term integrity of the caverns. The leaching effects were modeled here using the Sandia Solution Mining Code, SANSMIC. The modeling results indicate that leaching-induced features do not raise concern for the majority of the caverns. In addition to 12 caverns identified in previous leaching reports, seven caverns have been identified for further monitoring based on the results of this report. Twenty-two caverns had pre- and post-leach sonars that were compared with SANSMIC results. Overall, SANSMIC was able to capture the leaching well.
This report provides information on contaminant concentrations in multiple wildlife prey species inhabiting or associated with water bodies on and downstream from the Oak Ridge Reservation (ORR), including regional reference sites. This information can be used to understand the nature and extent of contaminant exposure and transfer through the food web and to provide a baseline for evaluating temporal trends in contaminant exposure and accumulation. This information was gathered as part of the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Five-Year Review (FYR) process, and it also addresses regulator comments on the annual Remediation Effectiveness Report (RER). This report summarizes the results of biological sampling completed in the spring and summer of 2020, prior to the 2021 FYR. Sampled locations included key sites upstream from the point sources of contaminants, along with watershed integration points on and off the ORR. Integration points are spatially the most important sampling sites because they capture biological responses to upstream contaminant inputs from both aqueous and groundwater sources, as well as responses to various remedial actions. These sites are most often located at a watershed administration unit boundary and may have regulatory significance for performance measures. In many cases, there are long-term biological and other monitoring data associated with these sites; these data generally fall within the areas of exposure and effects.
DOE maintains an up-to-date documentation of the number of available full drawdowns of each of the caverns at the Strategic Petroleum Reserve (SPR), where an available full drawdown is defined as the ability to move all the oil out from a cavern at full drawdown rates. This report covers impacts on drawdown availability due to SPR operations during Calendar Year 2024.
The US Department of Energy (DOE) Oak Ridge Reservation (ORR) is located in Anderson and Roane Counties, Tennessee. A portion of the ORR, known as Self-Sufficiency Parcel 2 (SSP2) is planned for transfer for private use. The SSP2 Site is approximately 670 acres (Figure 1-1), although the current plan is to only clear and develop a portion of this acreage. Any inquiries about the land transfer and future development should be directed to DOE Oak Ridge Environmental Management, as this is beyond the scope of the Natural Resources Management Team (NRMT). NRMT records bat data for the entire ORR, including acoustic monitoring, mist netting and cave surveys. A few surveys have previously been conducted for small land transfers adjacent to SSP2 (See Appendix A), but not for the entire SSP2 area. Since bats have a large range, it was decided that collecting data while SSP2 was still accessible would be beneficial for the NRMT dataset. Acoustic data was therefore collected within and near SSP2 during the summer of 2024. This write-up is not a Biological Assessment (BA). However, the data and information provided can be used during the creation of a BA and consultations with US Fish and Wildlife Service (USFWS) in order to comply with federal directives of the Endangered Species Act of 1973 (16 U. S. C. 153 et seq.). The SSP2 site was surveyed during summer roosting/maternity season of 2024 using ultrasonic acoustic monitors to record calls from all bat species whose home ranges include the ORR. Special note was taken for presence of Federally listed Endangered and Threatened (T&E) bat species, as well as bat species which are Proposed for Federal listing, Candidate for federal listing, and state listed. Summer roosting season, from May 15 to August 15, is crucial to forest-dwelling T&E bat species for rearing young and foraging. Results of these surveys indicate the presence of three Federally listed bat species: Gray bat (Myotis grisescens--Endangered), Indiana bat (Myotis sodalis--Endangered), and Northern long-eared bat (Myotis septentrionalis--Endangered). Two additional bat species were present on the SSP2 Site: Tricolored bat (Perimyotis subflavus--Proposed for Federal listing) and Little brown bat (Myotis lucifugus—Candidate for Federal listing).
Tracking vital signs accurately is critical for triaging a patient and ensuring timely therapeutic intervention. The patient’s status is often clouded by compensatory mechanisms that can mask injury severity. The compensatory reserve measurement (CRM) is a triaging tool derived from an arterial waveform that has been shown to allow for earlier detection of hemorrhagic shock. However, the deep-learning artificial neural networks developed for its estimation do not explain how specific arterial waveform elements lead to predicting CRM due to the large number of parameters needed to tune these models. Alternatively, we investigate how classical machine-learning models driven by specific features extracted from the arterial waveform can be used to estimate CRM. More than 50 features were extracted from human arterial blood pressure data sets collected during simulated hypovolemic shock resulting from exposure to progressive levels of lower body negative pressure. A bagged decision tree design using the ten most significant features was selected as optimal for CRM estimation. This resulted in an average root mean squared error in all test data of 0.171, similar to the error for a deep-learning CRM algorithm at 0.159. By separating the dataset into sub-groups based on the severity of simulated hypovolemic shock withstood, large subject variability was observed, and the key features identified for these sub-groups differed. This methodology could allow for the identification of unique features and machine-learning models to differentiate individuals with good compensatory mechanisms against hypovolemia from those that might be poor compensators, leading to improved triage of trauma patients and ultimately enhancing military and emergency medicine.
The Naval Weapons Industrial Reserve Plant (NWIRP) in McGregor, Texas began manufacturing explosives in 1980 and several hazardous chemicals were discovered in lakes and streams surrounding the site in 1998. Contaminants traveled to local lakes and streams much faster than initially predicted. This research estimated contaminant travel times and identified locations where monitoring wells should be installed to yield the greatest reductions in uncertainties in travel-time predictions. To this end, groundwater and particle-tracking models for NWIRP site were built to predict hydraulic heads and contaminant travel times. Next, parameter (hydraulic conductivities) uncertainties, parameter identifiabilities, observation (hydraulic heads) worth, and predictive (contaminant travel times) uncertainties were quantified. Parameter uncertainties were reduced by up to 92%; a total of 19 of 158 parameters were at least moderately identifiable; travel-time uncertainties were reduced up to 92%. Additionally, travel-time predictions and post-calibration parameter distributions were generated using the null-space Monte Carlo (NSMC) technique. NSMC predicted that conservative tracers exited the flow system within a year, which matches with field data. Finally, an observations-worth analysis found that additional 11 more measurements would reduce travel-time uncertainties by factors from 1.04 to 4.3 over existing data if monitoring wells were installed at the suggested locations.
Optimum coplanar flight between orbits accounting for inner reserve mass proportion to flight time
Monte Carlo method for computing Atlas/Centaur flight performance reserve
Computer program for evaluating flight performance reserve requirements for Centaur vehicle using Monte Carlo method
Lipid and glycogen reserves in humans during prolonged exercise
High energy fuels for supersonic transport reserves
High energy density electrolytic cell systems for multiple reserve electrochemical spacecraft power supplies
Feasibility of metal oxygen primary batteries for multiple reserve use
Reserve attention capacity of a pilot was calculated using a pilot model that allocates exclusive model attention according to the ranking of task urgency functions whose variables are tracking error and error rate. The modeled task consisted of tracking a maneuvering target aircraft both vertically and horizontally, and when possible, performing a diverting side task which was simulated by the precise positioning of an electrical stylus and modeled as a task of constant urgency in the attention allocation algorithm. The urgency of the single loop vertical task is simply the magnitude of the vertical tracking error, while the multiloop horizontal task requires a nonlinear urgency measure of error and error rate terms. Comparison of model results with flight simulation data verified the computed model statistics of tracking error of both axes, lateral and longitudinal stick amplitude and rate, and side task episodes. Full data for the simulation tracking statistics as well as the explicit equations and structure of the urgency function multiaxis pilot model are presented.