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DOE OSTI2023

baseflow: a MATLAB and GNU Octave package for baseflow recession analysis

baseflow is a MATLAB® toolbox designed for baseflow recession analysis, a technique used in hydrologic science to infer aquifer properties from streamflow. By leveraging widely available streamflow data, baseflow can be used to estimate aquifer properties such as hydraulic conductivity and drainable porosity over the modern instrumental stream gage record. The toolbox is intended for analysis of measured streamflow values recorded on a daily timestep, and is tailored for shallow, unconfined riparian aquifers that discharge groundwater laterally into adjacent streams. Additionally, baseflow can analyze the collective behavior of individual hillslope aquifers constituting hydrologic catchments, known as “watersheds”, from a nonlinear dynamical systems perspective. The toolbox incorporates recent advances in baseflow recession analysis to enable objective estimations of aquifer properties, and their sensitivity to methodological decisions, at both hillslope and catchment scales.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

The Utility of Satellites and Autonomous Remote Sensing Platforms for Monitoring Offshore Aquaculture Farms: A Case Study for Canopy Forming Kelps

The emerging sector of offshore kelp aquaculture represents an opportunity to produce biofuel feedstock to help meet growing energy demand. Giant kelp represents an attractive aquaculture crop due to its rapid growth and production, however precision farming over large scales is required to make this crop economically viable. These demands necessitate high frequency monitoring to ensure outplant success, maximum production, and optimum quality of harvested biomass, while the long distance from shore and large necessary scales of production makes in person monitoring impractical. Remote sensing offers a practical monitoring solution and nascent imaging technologies could be leveraged to provide daily products of the kelp canopy and subsurface structures over unprecedented spatial scales. Here, we evaluate the efficacy of remote sensing from satellites and aerial and underwater autonomous vehicles as potential monitoring platforms for offshore kelp aquaculture farms. Decadal-scale analyses of the Southern California Bight showed that high offshore summertime cloud cover restricts the ability of satellite sensors to provide high frequency direct monitoring of these farms. By contrast, daily monitoring of offshore farms using sensors mounted to aerial and underwater drones seems promising. Small Unoccupied Aircraft Systems (sUAS) carrying lightweight optical sensors can provide estimates of canopy area, density, and tissue nitrogen content on the time and space scales necessary for observing changes in this highly dynamic species. Underwater color imagery can be rapidly classified using deep learning models to identify kelp outplants on a longline farm and high acoustic returns of kelp pneumatocysts from side scan sonar imagery signal an ability to monitor the subsurface development of kelp fronds. Current sensing technologies can be used to develop additional machine learning and spectral algorithms to monitor outplant health and canopy macromolecular content, however future developments in vehicle and infrastructure technologies are necessary to reduce costs and transcend operational limitations for continuous deployment in an offshore setting.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A mountain-induced moist baroclinic wave test case for the dynamical cores of atmospheric general circulation models

Idealized test cases for the dynamical cores of atmospheric general circulation models are informative tools to assess the accuracy of the numerical designs and investigate the general characteristics of atmospheric motions. A new test case is introduced that is built upon a baroclinically unstable base state with an added orographic barrier. The topography is analytically prescribed and acts as a trigger of both baroclinic Rossby waves and inertia–gravity waves on a rotating, regular-sized planet. Both dry and idealized moist configurations are suggested. The latter utilizes the Kessler warm-rain precipitation scheme. The test case enhances the complexity of the existing test suite hierarchy and focuses on the impacts of two midlatitudinal mountain ridges on the circulation. Selected simulation examples from four dynamical cores are shown. These are the Spectral Element and Finite Volume dynamical cores, which are part of the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM), versions 2.1.3 and 2.2, and the Cubed-Sphere Finite Volume dynamical cores, which is new to CESM version 2.2. In addition, the Model for Prediction Across Scales (MPAS) is tested. The overall flow patterns agree well in the four dynamical cores, but the details can vary greatly. The examples highlight the broad palette of use cases for the test case and reveal physics–dynamics coupling issues.

58 GEOSCIENCES↗

NASA NTRS1985

Automated mesoscale winds derived from GOES multispectral imagery

An automated technique for extracting mesoscale winds from sequences of GOES visible infrared spin scan radiatiometer (VISSR) image pairs has been developed, tested extensively, and configured for quasi-real time research applications on the Atmospheric Sciences Division's research computing sytem. The entire system of computer codes was successfully vectorized for execution on an array processor resulting in job turnaround in less than 1 hour. An objective quality control system provides much greater than 99 percent accuracy in eliminating questionable wind estimates. Dynamical analysis of cloud wind divergence has revealed temporally consistent convergence centers on the meso-beta scale that are highly correlated with ongoing and future developing convective storms.

Wilson, G. S.↗

NASA NTRS1989

An intelligent data acquisition system for fluid mechanics research

This paper describes a novel data acquisition system for use with wind-tunnel probe-based measurements, which incorporates a degree of specific fluid dynamics knowledge into a simple expert system-like control program. The concept was developed with a rudimentary expert system coupled to a probe positioning mechanism operating in a small-scale research wind tunnel. The software consisted of two basic elements, a general-purpose data acquisition system and the rulebased control element to take and analyze data and supplying decisions as to where to measure, how many data points to take, and when to stop. The system was validated in an experiment involving a vortical flow field, showing that it was possible to increase the resolution of the experiment or, alternatively, reduce the total number of data points required, to achieve parity with the results of most conventional data acquisition approaches.

Cantwell, E. R.↗

NASA NTRS1994

Investigation of Moving Belt Radiator Technology Issues

The development of an advanced spacecraft radiator technology is reported. The moving belt radiator is a thermal radiator concept with the promise of lower specific mass (per kW rejected) than that afforded by existing technologies. The results of a parametric study to estimate radiator mass for future space power systems is presented. It is shown that this technology can be scaled up to 200 MW for higher rejection temperatures. Several aspects of the design concept are discussed, including the dynamics of a large rotating belt in microgravity. The results of a computer code developed to model the belt dynamics are presented. A series of one-g experiments to investigate the dynamics of small belts is described. A comprehensive test program to investigate belt dynamics in microgravity aboard the NASA KC-135 aircraft is discussed. It was found that the desired circular shape can readily be achieved in microgravity. It is also shown that a rotating belt is stable when subjected to simulated attitude control maneuvers. Heat exchanger design is also investigated. Several sealing concepts were examined experimentally, and are discussed. Overall heat transfer coefficients to the rotating belt are presented. Material properties for various belt materials, including screen meshes, are also presented. The results presented in this report indicate that the moving belt radiator concept is technically feasible.

Teagan, W. Peter↗

NASA NTRS1995

Simulation of the photogrammetric appendage structural dynamics experiment

The Photogrammetric Appendage Structural Dynamics Experiment (PASDE) uses six video cameras in the Space Shuttle cargo bay to measure vibration of the Russian Mir space station Kvant-ll solar array. It occurs on Shuttle/Mir docking mission STS-74 scheduled for launch in November 1995. The objective of PASDE is to demonstrate photogrammetric technology for measuring 'untargeted' spacecraft appendage structural dynamics. This paper discusses a pre-flight simulation test conducted in July 1995, focusing on the image processing aspects. The flight camera system recorded vibrations of a full-scale structural test article having grids of white lines on black background, similar in appearance to the Mir solar array. Using image correlation analysis, line intersections on the structure are tracked in the video recordings to resolutions of less than 0.1 pixel. Calibration and merging of multiple camera views generated 3-dimensional displacements from which structural modal parameters are then obtained.

Pappa, Richard S.↗

NASA NTRS2003

Performance Analysis of a Hybrid Overset Multi-Block Application on Multiple Architectures

This paper presents a detailed performance analysis of a multi-block overset grid compu- tational fluid dynamics app!ication on multiple state-of-the-art computer architectures. The application is implemented using a hybrid MPI+OpenMP programming paradigm that exploits both coarse and fine-grain parallelism; the former via MPI message passing and the latter via OpenMP directives. The hybrid model also extends the applicability of multi-block programs to large clusters of SNIP nodes by overcoming the restriction that the number of processors be less than the number of grid blocks. A key kernel of the application, namely the LU-SGS linear solver, had to be modified to enhance the performance of the hybrid approach on the target machines. Investigations were conducted on cacheless Cray SX6 vector processors, cache-based IBM Power3 and Power4 architectures, and single system image SGI Origin3000 platforms. Overall results for complex vortex dynamics simulations demonstrate that the SX6 achieves the highest performance and outperforms the RISC-based architectures; however, the best scaling performance was achieved on the Power3.

Djomehri, M. Jahed↗

NASA NTRS2009

An Intelligent Archive Testbed Incorporating Data Mining

Many significant advances have occurred during the last two decades in remote sensing instrumentation, computation, storage, and communication technology. A series of Earth observing satellites have been launched by U.S. and international agencies and have been operating and collecting global data on a regular basis. These advances have created a data rich environment for scientific research and applications. NASA s Earth Observing System (EOS) Data and Information System (EOSDIS) has been operational since August 1994 with support for pre-EOS data. Currently, EOSDIS supports all the EOS missions including Terra (1999), Aqua (2002), ICESat (2002) and Aura (2004). EOSDIS has been effectively capturing, processing and archiving several terabytes of standard data products each day. It has also been distributing these data products at a rate of several terabytes per day to a diverse and globally distributed user community (Ramapriyan et al. 2009). There are other NASA-sponsored data system activities including measurement-based systems such as the Ocean Data Processing System and the Precipitation Processing system, and several projects under the Research, Education and Applications Solutions Network (REASoN), Making Earth Science Data Records for Use in Research Environments (MEaSUREs), and the Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) programs. Together, these activities provide a rich set of resources constituting a value chain for users to obtain data at various levels ranging from raw radiances to interdisciplinary model outputs. The result has been a significant leap in our understanding of the Earth systems that all humans depend on for their enjoyment, livelihood, and survival. The trend in the community today is towards many distributed sets of providers of data and services. Despite this, visions for the future include users being able to locate, fuse and utilize data with location transparency and high degree of interoperability, and being able to convert data to information and usable knowledge in an efficient, convenient manner, aided significantly by automation (Ramapriyan et al. 2004; NASA 2005). We can look upon the distributed provider environment with capabilities to convert data to information and to knowledge as an Intelligent Archive in the Context of a Knowledge Building system (IA-KBS). Some of the key capabilities of an IA-KBS are: Virtual Product Generation, Significant Event Detection, Automated Data Quality Assessment, Large-Scale Data Mining, Dynamic Feedback Loop, and Data Discovery and Efficient Requesting (Ramapriyan et al. 2004).

Ramapriyan, H.↗

NASA NTRS2011

Hybrid CFD/CAA Modeling for Liftoff Acoustic Predictions

This paper presents development efforts at the NASA Marshall Space flight Center to establish a hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) simulation system for launch vehicle liftoff acoustics environment analysis. Acoustic prediction engineering tools based on empirical jet acoustic strength and directivity models or scaled historical measurements are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. CFD based modeling approaches are now able to capture the important details of vehicle specific plume flow environment, identifY the noise generation sources, and allow assessment of the influence of launch pad geometric details and sound mitigation measures such as water injection. However, CFD methodologies are numerically too dissipative to accurately capture the propagation of the acoustic waves in the large CFD models. The hybrid CFD/CAA approach combines the high-fidelity CFD analysis capable of identifYing the acoustic sources with a fast and efficient Boundary Element Method (BEM) that accurately propagates the acoustic field from the source locations. The BEM approach was chosen for its ability to properly account for reflections and scattering of acoustic waves from launch pad structures. The paper will present an overview of the technology components of the CFD/CAA framework and discuss plans for demonstration and validation against test data.

Strutzenberg, Louise L.↗

NASA NTRSDate not supplied

Modeling Ring-Opening Polymerization with Machine-Learned Committors

Many important industrial and biological processes depend on ring-opening polymerization (ROP), including large-scale production polymers, such as nylon 6, and a variety of biodegradable polymers and high-performance resins. Large-scale simulations (>200K atoms) of ROP were performed using a deep neural network-based method that captured the effect of the local chemical environment of the reactive sites using training data from quantum chemical methods. The utility of this method was demonstrated by modeling the cationic ROP of bis-benzoxazine, a promising resin for use in advanced high-temperature application composites (>200°C). Density functional theory calculations were used to map out the various ring opening and polymerization reaction paths that occur during the thermal processing of bis-benzoxazine. The probabilities of these reactions, as a function of local atomic configurations, were used to construct committor functions using a neural network approach. The learned committor functions were then used to determine when a particular reaction occurred within the REACTER framework for reactive molecular dynamics simulations. The experimentally observed exotherm that occurs during bis-benzoxazine ROP was captured in an effective manner in the simulations by imposing a local heating of the system that corresponds to the enthalpy of reaction for each reaction. The dependence of the final polymer morphology on the ROP reaction temperature was analyzed at the molecular scale. The results presented in this work indicate that machine-learned committor functions are a promising approach for incorporating high-fidelity reactivity criteria that capture the effect of local chemical environments into large-scale polymerization simulations.

machine learning, polymer simulations, molecular d↗

DOE OSTI2022

Global energy spectrum of the general oceanic circulation

Abstract Advent of satellite altimetry brought into focus the pervasiveness of mesoscale eddies $${{{{{{{\bf{{{{{{{{\mathcal{O}}}}}}}}}}}}}}}}({100})$$ O ( 100 ) km in size, which are the ocean’s analogue of weather systems and are often regarded as the spectral peak of kinetic energy (KE). Yet, understanding of the ocean’s spatial scales has been derived mostly from Fourier analysis in small "representative” regions that cannot capture the vast dynamic range at planetary scales. Here, we use a coarse-graining method to analyze scales much larger than what had been possible before. Spectra spanning over three decades of length-scales reveal the Antarctic Circumpolar Current as the spectral peak of the global extra-tropical circulation, at ≈ 10 4 km, and a previously unobserved power-law scaling over scales larger than 10 3 km. A smaller spectral peak exists at ≈ 300 km associated with mesoscales, which, due to their wider spread in wavenumber space, account for more than 50% of resolved surface KE globally. Seasonal cycles of length-scales exhibit a characteristic lag-time of ≈ 40 days per octave of length-scales such that in both hemispheres, KE at 10 2 km peaks in spring while KE at 10 3 km peaks in late summer. These results provide a new window for understanding the multiscale oceanic circulation within Earth’s climate system, including the largest planetary scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Superspin renormalization and slow relaxation in random spin systems

We develop an excited-state real-space renormalization group (RSRG-X) formalism to describe the dynamics of conserved densities in randomly interacting spin-12 systems. Our formalism is suitable for systems with U(1) and Z2 symmetries, and we apply it to chains of randomly positioned spins with dipolar XX+YY interactions, as arise in Rydberg quantum simulators and other platforms. The formalism generates a sequence of effective Hamiltonians that provide approximate descriptions for dynamics on successively smaller energy scales. These effective Hamiltonians involve “superspins”: two-level collective degrees of freedom constructed from (anti)aligned microscopic spins. Conserved densities can then be understood as relaxing via coherent collective spin flips. For the well-studied simpler case of randomly interacting nearest-neighbor XX+YY chains, the superspins reduce to single spins. Our formalism also leads to a numerical method capable of simulating the dynamics up to an otherwise inaccessible combination of large system size and late time. Focusing on disorder-averaged infinite-temperature autocorrelation functions, in particular the spin survival probability Sp¯(t), we demonstrate quantitative agreement between our algorithm and exact diagonalization (ED) at low but nonzero frequencies. Such agreement holds for chains with nearest-neighbor, next-nearest-neighbor, and long-range dipolar interactions. Our results indicate decay of Sp¯(t) slower than any power law and feature no significant deviation from the ∼1/ln2(t) asymptote expected from the infinite-randomness fixed-point of the nearest-neighbor model. We also apply the RSRG-X formalism to two-dimensional long-range systems of moderate size and find slow late-time decay of Sp¯(t).

Zhao, Yi J↗

NASA NTRS1999

Engineering of Novel Biocolloid Suspensions

Colloidal suspensions are materials with a variety of uses from cleaners and lubricants to food, cosmetics, and coatings. In addition, they can be used as a tool for testing the fundamental tenets of statistical physics. Colloidal suspensions can be synthesized from a wide variety of materials, and in the form of monodisperse particles, which can self-assemble into highly ordered colloidal crystal structures. As such they can also be used as templates for the construction of highly ordered materials. Materials design of colloids has, to date, relied on entropic self-assembly, where crystals form as result of lower free energy due to a transition to order. Here, our goal is to develop a completely new method for materials fabrication using colloidal precursors, in which the self-assembly of the ordered colloidal structures is driven by a highly controllable, attractive interaction. This will greatly increase the range of potential structures that can be fabricated with colloidal particles. In this work, we demonstrate that colloidal suspensions can be crosslinked through highly specific biological crosslinking reactions. In particular, the molecules we use are protein-carbohydrate interactions derived from the immune system. This different driving force for self-assembly will yield different and novel suspensions structures. Because the biological interactions are heterotypic (A binding to B), this chemical system can be used to make binary alloys in which the two colloid subpopulations vary in some property - size, density, volume fraction, magnetic susceptibility, etc. An additional feature of these molecules which is unique - even within the realm of biological recognition - is that the molecules bind reversibly on reasonable time-scales, which will enable the suspension to sample different configurations, and allow us to manipulate and measure the size of the suspension dynamically. Because of the wide variety of structures that can be made from these novel colloids, and because the suspension structure can be altered dynamically, we believe this biocolloid system will yield a novel set of materials with many technological applications, including sensors (both biological and non-biological), optical filters and separation media.

Hammer, D. A.↗

NASA NTRS2005

Intermittent Turbulence and SOC Dynamics in a 2-D Driven Current-Sheet Model

Borovsky et al. have shown that Earth's magnetotail plasma sheet is strongly turbulent. More recently, Borovsky and Funsten have shown that eddy turbulence dominates and have suggested that the eddy turbulence is driven by fast flows that act as jets in the plasma. Through basic considerations of energy and magnetic flux conservation, these fast flows are thought to be localized to small portions of the total plasma sheet and to be generated by magnetic flux reconnection that is similarly localized. Angelopoulos et al., using single spacecraft Geotail data, have shown that the plasma sheet turbulence exhibits signs of intermittence and Weygand et al., using four spacecraft Cluster data, have confirmed and expanded on this conclusion. Uritsky et al., using Polar UVI image data, have shown that the evolution of bright, nightside, UV auroral emission regions is consistent with many of the properties of systems in self-organized criticality (SOC). Klimas et al. have suggested that the auroral dynamics is a reflection of the dynamics of the fast flows in the plasma. sheet. Their hypothesis is that the transport of magnetic fludenergy through the magnetotail is enabled by scale-free avalanches of localized reconnection whose SOC dynamics are reflected in the auroral UV emission dynamics. A corollary of this hypothesis is that the strong, intermittent, eddy turbulence of the plasma sheet is closely related to its critical dynamics. The question then arises: Can in situ evidence for the SOC dynamics be found in the properties of the plasma sheet turbulence? A 2-dimensional numerical driven current-sheet model of the central plasma sheet has been developed that incorporates an idealized current-driven instability with a resistive MHD system. It has been shown that the model can evolve into SOC in a physically relevant parameter regime. Initial results from a study of intermittent turbulence in this model and the relationship of this turbulence to the model's known SOC dynamics will be discussed.

Klimas, A. J.↗

DOE OSTI2021

Facilitating better and faster simulations of aerosol-cloud interactions in Earth system models

Focal Area(s): 1. Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising a hierarchy of models. 2. Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: One major challenge that Earth system models (ESMs) face in providing credible prediction of the Earth system and its water cycle characteristics (e.g., mean state, variability, and extreme events) is to accurately simulate aerosol-cloud interactions (ACI). The physical, chemical, and dynamical processes affecting ACI are extremely complex and they range from nanoscale to planetary scale. In each model development cycle, scientists spend significant efforts investigating model deficiencies and uncertainties associated with aerosols (e.g., emissions, chemical processes, aerosol microphysics, and transport) and clouds (e.g., macrophysics, microphysics, turbulence, and large-scale circulation) in order to develop improved treatments. However, despite decades of active research, ACI is still a major source of uncertainty in climate projections, even though great progress has been made. Specific scientific challenges include: (i) Parameterizations are developed based on limited data; (ii) The complexity of a parameterization required for accurate predictions is not understood; (iii) Incomplete and unknown physics leads to errors in the fully coupled Earth system; and (iv) Complex physics is computationally too expensive to employ in ESMs.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2011

Dynamic Testing of the NASA Hypersonic Project Combined Cycle Engine Testbed for Mode Transition Experiments

NASA is interested in developing technology that leads to more routine, safe, and affordable access to space. Access to space using airbreathing propulsion systems has potential to meet these objectives based on Airbreathing Access to Space (AAS) system studies. To this end, the NASA Fundamental Aeronautics Program (FAP) Hypersonic Project is conducting fundamental research on a Turbine Based Combined Cycle (TBCC) propulsion system. The TBCC being studied considers a dual flow-path inlet system. One flow-path includes variable geometry to regulate airflow to a turbine engine cycle. The turbine cycle provides propulsion from take-off to supersonic flight. The second flow-path supports a dual-mode scramjet (DMSJ) cycle which would be initiated at supersonic speed to further accelerate the vehicle to hypersonic speed. For a TBCC propulsion system to accelerate a vehicle from supersonic to hypersonic speed, a critical enabling technology is the ability to safely and effectively transition from the turbine to the DMSJ-referred to as mode transition. To experimentally test methods of mode transition, a Combined Cycle Engine (CCE) Large-scale Inlet testbed was designed with two flow paths-a low speed flow-path sized for a turbine cycle and a high speed flow-path designed for a DMSJ. This testbed system is identified as the CCE Large-Scale Inlet for Mode Transition studies (CCE-LIMX). The test plan for the CCE-LIMX in the NASA Glenn Research Center (GRC) 10- by 10-ft Supersonic Wind Tunnel (10x10 SWT) is segmented into multiple phases. The first phase is a matrix of inlet characterization (IC) tests to evaluate the inlet performance and establish the mode transition schedule. The second phase is a matrix of dynamic system identification (SysID) experiments designed to support closed-loop control development at mode transition schedule operating points for the CCE-LIMX. The third phase includes a direct demonstration of controlled mode transition using a closed loop control system developed with the data obtained from the first two phases. Plans for a fourth phase include mode transition experiments with a turbine engine. This paper, focusing on the first two phases of experiments, presents developed operational and analysis tools for streamlined testing and data reduction procedures.

Source record↗

DOE OSTI2024

Characterizing the multisectoral impacts of future global hydrologic variability

There is significant uncertainty in how global water supply will evolve in the future, due to uncertain climate, socioeconomic, and land use change drivers and variability of hydrologic processes. It is critical to characterize the potential impacts of uncertainty in future water supply given its importance for food and energy production. In this work, we introduce a framework that integrates stochastic hydrology and human-environmental systems to characterize uncertainty in future water supply and its multisector impacts. We develop a global stochastic watershed model and demonstrate that this model can generate a large ensemble of realizations of basin-scale runoff with global coverage that preserves the mean, variance, and spatial correlation of a historical benchmark. We couple this model with a well-known human-environmental systems model to explore the impacts of runoff variability on the water and agricultural sectors across spatial scales. We find that the impacts of future hydrologic variability vary across sectors and regions. Impacts are felt most strongly in the water and agricultural sectors for basins that are expected to have unsustainable water use in the future, such as the Indus River basin. For this basin, we find that the variability in future irrigation water withdrawals and irrigated cropland increase over time due to uncertainty in renewable water supply. We also use the Indus basin to show how our stochastic ensemble can be leveraged to explore the global multisector consequences of local extreme runoff conditions. This work introduces a novel technique to explore the propagation of future hydrologic variability across human and natural systems and spatial scales.

54 ENVIRONMENTAL SCIENCES↗