Yellowstone Ecological Forecasting II: Assessing Change in Aspen Extent in Northern Yellowstone National Park
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Vanessa Bailey↗
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Assessing Change in Aspen Extent in Northern Yellowstone National Park
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Megan Rich↗
Tool for Analysis and Reduction of Scientific Data
The Automated Scheduling and Planning Environment (ASPEN) computer program has been updated to version 3.0. ASPEN as a whole (up to version 2.0) has been summarized, and selected aspects of ASPEN have been discussed in several previous NASA Tech Briefs articles. Restated briefly, ASPEN is a modular, reconfigurable, application software framework for solving batch problems that involve reasoning about time, activities, states, and resources. Applications of ASPEN can include planning spacecraft missions, scheduling of personnel, and managing supply chains, inventories, and production lines. ASPEN 3.0 can be customized for a wide range of applications and for a variety of computing environments that include various central processing units and randomaccess memories. Domain-specific reasoning modules (e.g., modules for determining orbits for spacecraft) can easily be plugged into ASPEN 3.0. Improvements over other, similar software that have been incorporated into ASPEN 3.0 include a provision for more expressive time-line values, new parsing capabilities afforded by an ASPEN language based on Extensible Markup Language, improved search capabilities, and improved interfaces to other, utility-type software (notably including MATLAB).
James, Mark↗
Opportunistic Short‐Term Water Uptake Dynamics by Subalpine Trees Observed via In Situ Water Isotope Measurements
Abstract Variations in tree water sources are important to understand in semi‐arid ecosystems because climatic shifts towards lower snowpack and increased drought affect water availability in subalpine forests of the western US. Here, we use daily in situ measurements of stable isotopes ( 2 H & 18 O) in soil and tree stem water, soil matric potential and sap flow to study tree water uptake dynamics. We instrumented three soil profiles down to 90 cm, as well as three aspen and engelmann spruce trees near Gothic, Colorado, in the East River watershed. We observed the fate of natural isotopic variations in rainfall, soil, and plants from June to October 2022, and in August 2023 we conducted a 2 H labeled irrigation experiment. Our observations showed that all studied aspen trees compensated for water scarcity in the shallow soil by shifting the dominant water source at 60(±20) cm to ⅔ of uptake from 90 cm within a few days of a dry period. Both species relied on snowmelt stored in the subsoil to sustain transpiration. Intense rainfall caused the plant water uptake to shift partially to top soil layers within 2 days. Spruce transpiration was lower and relied more on snowmelt, because rainfall infiltration was low in the spruce stand due to high canopy interception. Our findings highlight the important role of snowmelt stored in the deep soil layers for subalpine forest drought response and the dominant fate of monsoonal rainfall to become transpiration rather than recharging groundwater and streams in the Upper Colorado River. Plain Language Summary There is a need to understand how trees in mountainous regions respond to dry conditions that lead to water scarcity, because climate projections suggest that such conditions will become more frequent in the future. Here we present a novel data set of measurements of daily stable isotopes of water across soil profiles and in tree stems of aspen and spruce. Our data show that when the upper soil dried out, aspen trees shifted to using water from deeper layers (beneath 60 cm) to keep transpiring. For spruce trees the uptake pattern is less clear, but both types of trees mainly used snowmelt stored in the deeper soil layers to survive the dry summer. After heavy rain, aspen and spruce trees switched to using water from the top 20 cm of soil. However, for spruce, only some rain reached the soil because the dense tree canopy intercepted it, so spruce trees stayed more dependent on snowmelt and used less water overall. This study shows how important deep snowmelt water is for helping forests survive dry periods and suggests that most summer rain is quickly used by trees rather than replenishing streams and groundwater in the headwaters of the Colorado River. Key Points Tree water resources changed within a few days from snow dominated to higher share of rainfall as soils wetted up after a dry period Compensatory plant water uptake by aspen from the deep layer (90 cm), while uptake from soil depths that became drier (60 cm) declined Strong differences between water sources and availability beneath aspen and spruce, respectively
Sprenger, Matthias↗
Predictive Modeling and Diagnostic Monitoring of Extreme Science Workflows (Final Report)
This proposal addresses a critical issue of performance prediction identified in the report from the ASCR \Computational Modeling of Big Networks (COMBINE)" workshop: "end-to-end performance is not predictable due to a variety of factors. Even when some performance forecasts or predictions can be made, they often cannot explain the reasons why some predictions fail." We will develop new analytical models to predict the end-to-end performance of scientific workflows on DOE computing infrastructures, and use simulations and experimentation to validate and refine these models, as well as to pinpoint the sources of model inaccuracy. We will also use these models to help diagnose application and infrastructure problems, and to adapt the system based on this diagnosis. This section provides background in the areas relevant to the proposed work. RPI’s specific tasks within the Panorama project are as follows: (1) Develop Aspen-Simulation interface for Workflow Model Driven Simulation. (2) Validate manual performance models of two target workflow scenarios with empirical measurement and simulation. (3) Extend ROSS-Aspen API to simulate workflow descriptions when required. (4) Validate Aspen performance models of two target workflow scenarios with automatic performance model empirical measurement and simulation. (5) Design and implement final system to automatically generate Aspen performance models from workflow descriptions (including methods to compensate for limitations of Aspen analytical models). (6) Validate improved Aspen performance models with target workflow on production infrastructure. To date, all the project milestones assigned to us where reached within the best of our abilities over the course of the project performance period. Below describes the key outcome from our collaborative research in a system named, Durango .
97 MATHEMATICS AND COMPUTING↗
Detection of aspen/conifer forest mixes from multitemporal Landsat digital data
Aspen, conifer and mixed aspen/conifer forests were mapped for a 15-quadrangle study area in the Utah-Idaho Bear River Range using Landsat multispectral scanner data. Digital classification and statistical analysis of Landsat data allowed the identification of six groups of signatures which reflect different types of aspen/conifer forest mixing. Photo interpretations of the print symbols suggest that such classes are indicative of mid to late seral aspen forests. Digital print map overlayes and acreage calculations were prepared for the study area quadrangles. Further field verification is needed to acquire additional information about the nature of the forests. Single data Landsat analysis should be a cost effective means to index aspen forests which are at least in the mid seral phase of conifer invasion. Since aspen canopies tend to obscure understory conifers for early seral forests, a second data analysis, using data taken when aspens are leafless, could provide information about early seral aspen forests.
Merola, J. A.↗
Accurate numerical simulations of open quantum systems using spectral tensor trains
Decoherence between qubits is a major bottleneck in quantum computations. Decoherence results from intrinsic quantum and thermal fluctuations as well as noise in the external fields that perform the measurement and preparation processes. With prescribed colored noise spectra for intrinsic and extrinsic noise, we present a numerical method, Quantum Accelerated Stochastic Propagator Evaluation (Q-ASPEN), to solve the time-dependent noise-averaged reduced density matrix in the presence of intrinsic and extrinsic noise. Q-ASPEN is arbitrarily accurate and can be applied to provide estimates for the resources needed to error-correct quantum computations. We employ spectral tensor trains, which combine the advantages of tensor networks and pseudospectral methods, as a variational ansatz to the quantum relaxation problem and optimize the ansatz using methods typically used to train neural networks. Here, the spectral tensor trains in Q-ASPEN make accurate calculations with tens of quantum levels feasible. We present benchmarks for Q-ASPEN on the spin-boson model in the presence of intrinsic noise and on a quantum chain of up to 32 sites in the presence of extrinsic noise. In our benchmark, the memory cost of Q-ASPEN scales as a low-order polynomial in the size of the system once the number of system states surpasses the number of basis functions used in the spectral expansion.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
BIOASPEN: System for technology development
The public version of ASPEN was installed in the VAX 11/750 computer. To examine the idea of BIOASPEN, a test example (the manufacture of acetone, butanol, and ethanol through a biological route) was chosen for simulation. Previous reports on the BIOASPEN project revealed the limitations of ASPEN in modeling this process. To overcome some of the difficulties, modules were written for the acid and enzyme hydrolyzers, the fermentor, and a sterilizer. Information required for these modules was obtained from the literature whenever possible. Additional support modules necessary for interfacing with ASPEN were also written. Some of ASPEN subroutines were themselves altered in order to ensure the correct running of the simulation program. After testing of these additions and charges was completed, the Acetone-Butanol-Ethanol (ABE) process was simulated. A release of ASPEN (which contained the Economic Subsystem) was obtained and installed. This subsection was tested and numerous charges were made in the FORTRAN code. Capital investment and operating cost studies were performed on the ABE process. Some alternatives in certain steps of the ABE simulation were investigated in order to elucidate their effects on the overall economics of the process.
Source record↗
Persistent Effects of Fire Severity on Early Successional Forests in Interior Alaska
There has been a recent increase in the frequency and extent of wildfires in interior Alaska, and this trend is predicted to continue under a warming climate. Although less well documented, corresponding increases in fire severity are expected. Previous research from boreal forests in Alaska and western Canada indicate that severe fire promotes the recruitment of deciduous tree species and decreases the relative abundance of black spruce (Picea mariana) immediately after fire. Here we extend these observations by (1) examining changes in patterns of aspen and spruce density and biomass that occurred during the first two decades of post-fire succession, and (2) comparing patterns of tree composition in relation to variations in post-fire organic layer depth in four burned black spruce forests in interior Alaska after 10-20 years of succession.Wefound that initial effects of fire severity on recruitment and establishment of aspen and black spruce were maintained by subsequent effects of organic layer depth and initial plant biomass on plant growth during post-fire succession. The proportional contribution of aspen (Populus tremuloides) to total stand biomass remained above 90% during the first and second decades of succession in severely burned sites, while in lightly burned sites the proportional contribution of aspen was reduced due to a 40- fold increase in spruce biomass in these sites. Relationships between organic layer depth and stem density and biomass were consistently negative for aspen, and positive or neutral for black spruce in all four burns. Our results suggest that initial effects of post-fire organic layer depths on deciduous recruitment are likely to translate into a prolonged phase of deciduous dominance during post-fire succession in severely burned stands. This shift in vegetation distribution has important implications for climate-albedo feedbacks, future fire regime, wildlife habitat quality and natural resources for indigenous subsistence activities in interior Alaska.
Shenoy, Aditi↗
Using Grover’s search protocol to select the best qubit pairs
This research represents a continuation of our investigation of the Rigetti quantum platform as part of the Quantum Leap for Fusion Energy Sciences project. We evaluate the performance of the new Aspen-11, Aspen-M-2, Aspen-M-3 quantum processing units (QPU) through the application of the Grover’s search algorithm and the validation of single gate fidelities. The performance of the new QPUs is compared to the older Aspen-7 device, and it is shown that qubit pair selection plays a key role in the optimization process. Additionally, we delve into the examination of coherent and decoherent errors associated with native gates. To optimize our approach, we have developed several relatively inexpensive hardware protocols aimed at facilitating the selection of the most suitable qubit pairs. These protocols involve running various circuits on the hardware and assessing the overall performance of the tested qubit pairs. Through these protocols, we have demonstrated that the quality of qubit pairs on a single chip can exhibit significant variations.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
BOREAS TE-10 Leaf Optical Properties
The Boreal Ecosystem-Atmospheric Study (BOREAS) TE-10 (Terrestrial Ecology) team collected several data sets in support of its efforts to characterize and interpret information on the reflectance, transmittance, gas exchange, oxygen evolution, and biochemical properties of boreal vegetation. This data set describes the spectral optical properties (reflectance and transmittance) of boreal forest conifers and broadleaf tree leaves as measured with a Spectron Engineering SE590 spectroradiometer at the Southern Study Area Old Black Spruce (SSA OBS), Old Jack Pine (OJP), Young Jack Pine (YJP), Old Aspen (OA), Old Aspen Auxiliary (OA-AUX), Young Aspen Auxiliary (YA-AUX), and Young Aspen (YA) sites. The data were collected during the growing seasons of 1994 and 1996 and are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
Hall, Forrest G.↗
Produced Water and Waste Heat-aided Blowdown Water Treatment: Using Chemical and Energy Synergisms for Value Creation
The project objective was to develop a cooling blowdown water (BDW) treatment process utilizing produced water (PW) and low-grade heat to maximize water reuse and saleable by-product generation while reducing chemical and energy footprints of the treatment. The proposed treatment process consists of mixing, softening, organics and suspended solids removal, reverse osmosis (RO), thermal desalination, and brine electrolysis. BDW samples collected from a local coal-fired power plant and PW samples from two shale gas production wells were used in this study. Each treatment unit was first designed and tested to quantify its treatment efficiency, and its chemical and energy requirements. In addition, a process model was developed and model simulations were conducted based on the experimental results and literature data to optimize the treatment process. A techno-economic analysis was conducted to quantify chemical and energy savings as well as production of 10-lb brine as a saleable product. With the field-collected BDW and PW samples, mixing experiments determined a volumetric mixing ratio 10:1 (BDW:PW) resulted in the best performance of multivalent ions removal and largest chemical savings for softening. Softening of the BDW/PW mixtures using alkaline chemicals (Na 2 CO 3 and NaOH) achieved 95%-100% removal of scaling-forming cations (Ca, Mg, Fe, Ba, Sr) and 60% of silicon, and 10% of total organic carbon (TOC). The mixing and softening treatments yielded an effluent with total dissolved solids (TDS) concentration of 23 g/L. Activated carbon (AC) filtration removed TOC to a low level (< 3 mg/L) and further removed remaining scale-forming divalent metals and silica from the softened water. The AC filtration resulted in a slight reduction of TDS from 23 g/L to 20 g/L, leaving behind only mostly monovalent ions (i.e., sodium and chloride) in the filtered water. These pretreatments yielded a feed water that met the criteria of the downstream reverse osmosis (RO) to prevent membrane fouling. A cross-flow RO system was used to further concentrate the TDS of the AC effluent. Various factors including TDS, pH, and applied pressure were examined and optimal conditions were determined for the co-treatment process. An integrated process consisting of mixing, softening, AC filtration and RO was used to treat a continuous flow (0.25 – 1.2 L/min, or 0.07 – 0.32 gpm) and successfully generated RO permeate as product water (TDS < 0.5 g/L) for reuse in cooling operation, and a concentrate (TDS ~ 45 g/L) to be further treated in a thermal desalination unit. These flow rates meet the FOA’s criterion of 0.01 – 1 gpm. Overall, the co-treatment of BDW/PW allowed shorter ramp-up time compared to treatment of BDW alone. It resulted in 40% and 55% savings of Na 2 CO 3(s) and NaOH, respectively, compared to treating the BDW and PW individually for the same level of softening. The co-treatment also resulted in a 29% energy saving compared to treatment of BDW only for the level of TDS concentration. A thermal desalination system was designed using CFD simulations and manufactured in the WVU Innovation Hub for further treatment of the RO concentrate to generate 10-lb brine. The system has a design flow rate of 2 gpm and has been successfully tested. A bench-scale brine electrolysis system was developed for on-site generation of chlorine/hypochlorite (Cl 2 /OCl - ) and caustic soda (NaOH) as useful chemicals for the co-treatment process. Using salt solutions (0.5 M and 1 M), the system achieved faradaic efficiencies of 93%-97% and 70%-77% for caustic soda and chlorine/hypochlorite generation, respectively. An economic analysis showed that the electricity costs for on-site generation of these chemicals were significantly lower than the chemical prices offered by suppliers. An industrial-scale process model consisting of mixing, softening, AC filtration, RO, thermal desalination, and brine electrolysis was developed using the Aspen Plus V9 in conjunction with Aspen Custom Modeler V9. The model serves as a solvable Aspen Plus model and as basis to form the costing infrastructure. In addition, techno-economic analysis considering capital, operating, and transportation costs was conducted. An optimization solution showed that produced water for mixing is still advantageous in low quantities. The optimum solution approaches a leveled cost of water (LCW) of 2 $/m 3 which becomes cost competitive with nominal water treatment prices.
20 FOSSIL-FUELED POWER PLANTS↗
Use Cases and Model Development of Thermal Storage Coupling for Advanced Nuclear Reactors
This report discusses the different options for coupling thermal energy storage (TES) systems to advanced nuclear power plants (A-NPPs) in order to enable flexible and hybrid plant operation. An advanced light-water reactor (ALWR) and a high-temperature gas-cooled reactor (HTGR) were selected as the initial use cases for demonstrating a thermally balanced energy storage coupling design for thermal power extraction. Cost functions for the A-LWR were derived from the fully balanced models that were developed based on three different coupling options with three different thermal energy bypass ratios. For the next steps, cost functions for the HTGR will also be derived, and additional nuclear reactors (e.g., a liquid-cooled fast reactor [LFR] or molten-salt reactor [MSR]) will be evaluated for coupling with TES in similar fashion, including the evaluation of their steady-state condition models and cost functions. The models presented herein showcase several design considerations, focusing on optimal deployment methodologies for achieving steady-state operation with minimum disruption to the nuclear power generation cycle. This report presents the results of steady state models developed using Aspen HYSYS®, wherein the thermal energy bypass for an NPP-TES coupling was varied up to 50%. The various components were sized using Aspen Process Economic Analyzer (APEA) and Aspen Exchanger Design and Rating (EDR), when applicable. Cost functions from these models were developed using the latest publicly available data obtained from APEA V11. The current steady-state models and cost functions provide a baseline for additional work focusing on dynamic operation and process optimization by using Idaho National Laboratory (INL)’s Framework for Optimization of Resources and Economics (FORCE) tools to evaluate the technoeconomic viability and transient operations of TES-coupled A-NPPs.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Multilevel Analysis, Design, and Modeling of Coupling Advanced Nuclear Reactors and Thermal Energy Storage in an Integrated Energy System
This report discusses the different options for coupling thermal energy storage (TES) systems to advanced nuclear power plants (A-NPPs) in order to enable flexible and hybrid plant operation. An advanced light-water reactor (A LWR), a high-temperature gas-cooled reactor (HTGR) and a liquid-metal fast reactor (LMFR) were selected as the initial use cases for demonstrating a thermally balanced energy storage coupling design for thermal power extraction. The models presented herein showcase several design considerations, focusing on optimal deployment methodologies for achieving steady-state and transient-state operation with minimum disruption to the nuclear power cycle. This first part of the study presents steady-state models developed using Aspen HYSYS®, with the thermal energy bypass for NPP-TES coupling being varied at up to 50%. The various components were sized using the Aspen Process Economic Analyzer (APEA) and Aspen Exchanger Design and Rating (EDR), when applicable. Cost functions from these models were developed using the latest publicly available data obtained from APEA V11. The TES-coupled A-NPP steady-state models and cost functions then provided a baseline for dynamic operation and process optimization by using Idaho National Laboratory (INL)’s Framework for Optimization of Resources and Economics (FORCE) tools. A stochastic optimization of the various energy storage systems coupled to the A-NPPs was then performed using the Risk Analysis Virtual Environment (RAVEN) and its dispatch optimization plugin, the Holistic Energy Resource Optimization Network (HERON). The signal processing and synthetic history capabilities of RAVEN were used to account for the unpredictable behavior of electricity markets. An autoregressive moving average (ARMA) model was used to analyze price signals from the Pennsylvania-New Jersey-Maryland (PJM) market and were applied to the HERON analysis in order to optimize a system with the best economics. Transient modeling evaluation was then performed using Modelica models within the HYBRID repository, which was developed at INL for the Department of Energy Integrated Energy Systems program for the characterization of dynamic integrated system behavior and feedback. This includes evaluation of the TES-coupled A-LWR systems’ impact on physical and thermal system response during imposed system demands. Additional TES-coupled reactor types, coupling approaches, markets, and TES technologies will be evaluated in future work.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Thermal Integration of Advanced Nuclear Reactors with a Reference Refinery, Methanol Synthesis, and a Wood Pulp Plant (Rev.1)
The present report is intended to provide process flow diagrams (PFDs) and energy and mass balance data sheets for a U.S. industrial sector subset with which nuclear heat and power could be integrated—a subset that includes the oil refining, methanol and pulp and paper industries. Coupling options for integrating nuclear energy into these industries are quantitatively outlined for reference systems, and future work will extend this analysis in greater detail. Opportunities for integrating small modular nuclear reactors (SMNRs) were investigated for each of the industrial process configurations. Aspen HYSYS and Cycle-Tempo models for a high-temperature gas-cooled reactor were developed to evaluate the proposed integration. This introductory evaluation provides a general description and assessment of the operating principles, reactor coolant core outlet temperature, and reactor size to be integrated with industry. The industrial processes of oil refining and the production of methanol, pulp and paper were simulated by using Aspen HYSYS, Aspen Plus, and the PRELIM (Petroleum Refinery Life Cycle Inventory Model) tool to develop process details. Cycle-Tempo models then extend the process modeling results to obtain net energy demands (e.g., heat, steam, and electricity) when accounting for process steam and waste heat recovery. This information is intended to foster the analysis of integrating an SMNR to decarbonize industrial facilities. The SMNR would provide reliable, competitive, and sustainable clean energy while reducing carbon emissions and other environmental impacts, such as water withdrawals, consumption, and contamination. The refining industry, exhibited in Figure ES1, is a leading consumer of fossil -fuel-based heat, power, and hydrogen in the U.S. industrial sector, generating over 164 million metric tons (MMT) of CO 2 emissions in 2023. The overall mass and energy pertaining to a generalized complex refinery in the United States is reflected in Figure ES1, along with energy metrics regarding integration with a nuclear power plant (NPP). Data sheets were developed to indicate the energy requirements for the overall refinery and each refinery process. The data sheet for the overall refinery is shown in Table ES2.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Functional Imaging of Microbial Interactions With Tree Roots Using a Microfluidics Setup
Coupling microfluidics with microscopy has emerged as a powerful approach to study at cellular resolution the dynamics in plant physiology and root-microbe interactions (RMIs). Most devices have been designed to study the model plant Arabidopsis thaliana at higher throughput than conventional methods. However, there is a need for microfluidic devices which enable in vivo studies of root development and RMIs in woody plants. Here, we developed the RMI-chip, a simple microfluidic setup in which Populus tremuloides (aspen tree) seedlings can grow for over a month, allowing continuous microscopic observation of interactions between live roots and rhizobacteria. We find that the colonization of growing aspen roots by Pseudomonas fluorescens in the RMI-chip involves dynamic biofilm formation and dispersal, in keeping with previous observations in a different experimental set-up. Also, we find that whole-cell biosensors based on the rhizobacterium Bacillus subtilis can be used to monitor compositional changes in the rhizosphere but that the application of these biosensors is limited by their efficiency at colonizing aspen roots and persisting. These results indicate that functional imaging of dynamic root-bacteria interactions in the RMI-chip requires careful matching between the host plant and the bacterial root colonizer.
59 BASIC BIOLOGICAL SCIENCES↗
Identifying environmental features for land management decisions
Advances in digital processing of LANDSAT imagery and in the interpretation of aerial photography are reported as well as the development of a geographic information system and the acquisition of cartographic equipment. Services to technical specialists and dignitaries are also described. The status of the following studies is discussed: Farmington Bay waterfowl; Sevier River wetland and agriculture; Davis County foothill development; Bear River Range aspen habitat; Wasatch-Cache riparian habitats; irrigated acreage in the Bear River Basin; the Parker Mountain rangeland inventory; and the development of techniques for inventorying aspen and aspen conifer stands. The cooperative project with NASA-Ames to verify LANDSAT digital maps of the forest and range resources on the LaSal Mountains is also considered.
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Automated Planning for a Deep Space Communications Station
This paper describes the application of Artificial Intelligence planning techniques to the problem of antenna track plan generation for a NASA Deep Space Communications Station. Me described system enables an antenna communications station to automatically respond to a set of tracking goals by correctly configuring the appropriate hardware and software to provide the requested communication services. To perform this task, the Automated Scheduling and Planning Environment (ASPEN) has been applied to automatically produce antenna trucking plans that are tailored to support a set of input goals. In this paper, we describe the antenna automation problem, the ASPEN planning and scheduling system, how ASPEN is used to generate antenna track plans, the results of several technology demonstrations, and future work utilizing dynamic planning technology.
Estlin, Tara↗