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DOE OSTI2024

Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective

Stoichiometric genome-scale metabolic models (generally abbreviated GSM, GSMM, or GEM) have had many applications in exploring phenotypes and guiding metabolic engineering interventions. Nevertheless, these models and predictions thereof can become limited as they do not directly account for protein cost, enzyme kinetics, and cell surface or volume proteome limitations. Lack of such mechanistic detail could lead to overly optimistic predictions and engineered strains. Initial efforts to correct these deficiencies were by the application of precursor tools for GSMs, such as flux balance analysis with molecular crowding. In the past decade, several frameworks have been introduced to incorporate proteome-related limitations using a genome-scale stoichiometric model as the reconstruction basis, which herein are called resource allocation models (RAMs). This review provides a broad overview of representative or commonly used existing RAM frameworks. This review discusses increasingly complex models, beginning with stoichiometric models to precursor to RAM frameworks to existing RAM frameworks. RAM frameworks are broadly divided into two categories: coarse-grained and fine-grained, with different strengths and challenges. Discussion includes pinpointing their utility, data needs, highlighting framework strengths and limitations, and appropriateness to various research endeavors, largely through contrasting their mathematical frameworks. Finally, promising future applications of RAMs are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1991

Computational simulation of acoustic fatigue for hot composite structures

This paper presents predictive methods/codes for computational simulation of acoustic fatigue resistance of hot composite structures subjected to acoustic excitation emanating from an adjacent vibrating component. Select codes developed over the past two decades at the NASA Lewis Research Center are used. The codes include computation of (1) acoustic noise generated from a vibrating component, (2) degradation in material properties of the composite laminate at use temperature, (3) dynamic response of acoustically excited hot multilayered composite structure, (4) degradation in the first-ply strength of the excited structure due to acoustic loading, and (5) acoustic fatigue resistance of the excited structure, including propulsion environment. Effects of the laminate lay-up and environment on the acoustic fatigue life are evaluated. The results show that, by keeping the angled plies on the outer surface of the laminate, a substantial increase in the acoustic fatigue life is obtained. The effect of environment (temperature and moisure) is to relieve the residual stresses leading to an increase in the acoustic fatigue life of the excited panel.

Singhal, S. N.↗

NASA NTRS1991

Gamma-ray line and anomalous continuum emission from the Crab

The observations of transient gamma-ray line and sporadic continuum emissions from the Crab over the last two decades are reviewed, and these measurements are used to explore the emission mechanisms and regions. When examined in detail, the measurements require an emission region(s) considerably more complex than predicted by simple synchrotron models, suggesting behavior reminiscent of gamma-ray bursts.

Owens, Alan↗

NASA NTRS2007

Optimization of Acoustic Pressure Measurements for Impedance Eduction

As noise constraints become increasingly stringent, there is continued emphasis on the development of improved acoustic liner concepts to reduce the amount of fan noise radiated to communities surrounding airports. As a result, multiple analytical prediction tools and experimental rigs have been developed by industry and academia to support liner evaluation. NASA Langley has also placed considerable effort in this area over the last three decades. More recently, a finite element code (Q3D) based on a quasi-3D implementation of the convected Helmholtz equation has been combined with measured data acquired in the Langley Grazing Incidence Tube (GIT) to reduce liner impedance in the presence of grazing flow. A new Curved Duct Test Rig (CDTR) has also been developed to allow evaluation of liners in the presence of grazing flow and controlled, higher-order modes, with straight and curved waveguides. Upgraded versions of each of these two test rigs are expected to begin operation by early 2008. The Grazing Flow Impedance Tube (GFIT) will replace the GIT, and additional capabilities will be incorporated into the CDTR. The current investigation uses the Q3D finite element code to evaluate some of the key capabilities of these two test rigs. First, the Q3D code is used to evaluate the microphone distribution designed for the GFIT. Liners ranging in length from 51 to 610 mm are investigated to determine whether acceptable impedance eduction can be achieved with microphones placed on the wall opposite the liner. This analysis indicates the best results are achieved for liner lengths of at least 203 mm. Next, the effects of moving this GFIT microphone array to the wall adjacent to the liner are evaluated, and acceptable results are achieved if the microphones are placed off the centerline. Finally, the code is used to investigate potential microphone placements in the CDTR rigid wall adjacent to the wall containing an acoustic liner, to determine if sufficient fidelity can be achieved with 32 microphones available for this purpose. Initial results indicate 32 microphones can provide acceptable measurements to support impedance eduction with this test rig.

Jones, M. G.↗

NASA NTRS2011

Design and Measurements of Dual-Polarized Wideband Constant-Beamwidth Quadruple-Ridged Flared Horn

A quad-ridged, flared horn achieving nearly constant beamwidth and excellent return loss over a 6:1 frequency bandwidth is presented. Radiation pattern measurements show excellent beamwidth stability from 2 to 12 GHz. Measured return loss is > 10 dB over the entire band and > 15 dB from 2.5 to 11 GHz. Using a custom physical optics code, system performance of a radio telescope is computed and predicted performance is average 70% aperture efficiency and 10 Kelvin of antenna noise temperature.

decade bandwidth↗

NASA NTRS2011

Warm and Saline Events Embedded in the Meridional Circulation of the Northern North Atlantic

Ocean state estimates from 1958 to 2005 from the Simple Ocean Assimilation System (SODA) system are analyzed to understand circulation between subtropical and subpolar Atlantic and their connection with atmospheric forcing. This analysis shows three periods (1960s, around 1980, and 2000s) with enhanced warm, saline waters reaching high latitudes, alternating with freshwater events originating at high latitudes. It complements surface drifter and altimetry data showing the subtropical -subpolar exchange leading to a significant temperature and salinity increase in the northeast Atlantic after 2001. The warm water limb of the Atlantic meridional overturning cell represented by SODA expanded in density/salinity space during these warm events. Tracer simulations using SODA velocities also show decadal variation of the Gulf Stream waters reaching the subpolar gyre and Nordic seas. The negative phase of the North Atlantic Oscillation index, usually invoked in such variability, fails to predict the warming and salinization in the early 2000s, with salinities not seen since the 1960s. Wind stress curl variability provided a linkage to this subtropical/subpolar gyre exchange as illustrated using an idealized two ]layer circulation model. The ocean response to the modulation of the climatological wind stress curl pattern was found to be such that the northward penetration of subtropical tracers is enhanced when amplitude of the wind stress curl is weaker than normal. In this case both the subtropical and subpolar gyres weaken and the subpolar density surfaces relax; hence, the polar front moves westward, opening an enhanced northward access of the subtropical waters in the eastern boundary current.

Hakkinen, Sirpa↗

NASA NTRS2017

Automation Rover for Extreme Environments

Almost 2,300 years ago the ancient Greeks built the Antikythera automaton. This purely mechanical computer accurately predicted past and future astronomical events long before electronics existed1. Automata have been credibly used for hundreds of years as computers, art pieces, and clocks. However, in the past several decades automata have become less popular as the capabilities of electronics increased, leaving them an unexplored solution for robotic spacecraft. The Automaton Rover for Extreme Environments (AREE) proposes an exciting paradigm shift from electronics to a fully mechanical system, enabling longitudinal exploration of the most extreme environments within the solar system.

automata↗

DOE OSTI2025

HydroForecast Long-term: Improving hydropower’s resilience to climate change through accurate climate-scale

With hydrologic patterns and water availability across the globe shifting due to climate change, advancements in hydrologic prediction systems can help significantly reduce the uncertainties that utilities and water supply entities have in their decision making. Understanding and estimating hydrology at the climate scale is critical for managing water resources under changing climate scenarios. This project focuses on integrating state-of-the-art neural network modeling with downscaled climate projections to deliver the reliable water supply projections decades into the future to meet an urgent need from hydropower operators and water utilities. In this Phase 1 DOE SBIR proposal, we developed and validated a theory-guided neural network model, HydroForecast Long-term, for climate-scale hydrology and implemented the model within existing HydroForecast infrastructure. HydroForecast Long-term combines the most accurate streamflow modeling system with a flexible and scalable data architecture to generate water supply projections out to the year 2100. This report illustrates that we have achieved our four objectives: 1) create a prototype of HydroForecast Long-term, building the neural network prediction model, 2) build an automated data input pipeline that processes large amounts of data from the latest global temperature and precipitation climate models; 3) benchmark the accuracy of the hydrologic model over the recent two decades over a large set of diverse basins, and 4) create a set of output visuals and summary metrics informed by customer feedback that connect the data to critical decision points. This work empowers water users to make data-informed decisions supporting a resilient, renewable-powered grid and water system. The results advance the Department of Energy’s mission by addressing critical gaps in water supply planning under climate change.

13 HYDRO ENERGY↗

DOE OSTI2025

Coupled Hydrological-Thermal-Biogeochemical Modeling for Predicting Arctic Carbon Emissions (CH4PACE)

The Arctic, with nearly 1,700 billion metric tons of carbon stored in its soils, is experiencing significant warming trends that raise concerns about the potential release of greenhouse gases, particularly methane. This report investigates the conversion of carbon stored in Arctic soils and permafrost into methane and its subsequent atmospheric release over the coming decades. Recent data indicate a rise in global methane concentrations, highlighting the importance of understanding the mechanisms of methane generation under anaerobic conditions prevalent in thawing permafrost. Our study employs a multi-faceted approach that integrates fieldwork, benchtop experiments, and numerical simulations to explore the subsurface hydrological-thermal-biogeochemical systems influencing methane emissions. We focus on the relationship between microbial activity in decomposing organic matter under oxygen-limited conditions and the transport of methane out of these saturated wetland soils. Key hydrological parameters, including permeability, porosity, and thermal conductivity, were measured on soil samples from Fairbanks, Alaska, and used to parameterize PFLOTRAN, a coupled hydrological-thermal-reactive transport simulator. Our model enables prediction of the evolution of the active layer and its impact on methane production and release. Our findings underscore the critical need for a mechanistic understanding of methane dynamics in permafrost environments to improve predictions of methane emissions in Earth systems models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Uncertainty Quantification in Atomistic Modeling of Metals and Its Effect on Mesoscale and Continuum Modeling: A Review

The design of next-generation alloys through the integrated computational materials engineering (ICME) approach relies on multiscale computer simulations to provide thermodynamic properties when experiments are difficult to conduct. Atomistic methods such as density functional theory (DFT) and molecular dynamics (MD) have been successful in predicting properties of never before studied compounds or phases. However, uncertainty quantification (UQ) of DFT and MD results is rarely reported due to computational and UQ methodology challenges. Over the past decade, studies that mitigate this gap have emerged. These advances are reviewed in the context of thermodynamic modeling and information exchange with mesoscale methods such as the phase-field method (PFM) and calculation of phase diagrams (CALPHAD). The importance of UQ is illustrated using properties of metals, with aluminum as an example, and highlighting deterministic, frequentist, and Bayesian methodologies. Finally, challenges facing routine uncertainty quantification and an outlook on addressing them are also presented.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Accelerating Computational Materials Discovery with Machine Learning and Cloud High-Performance Computing: from Large-Scale Screening to Experimental Validation

High-throughput computational materials discovery has promised significant acceleration of the design and discovery of new materials for many years. Despite a surge in interest and activity, the constraints imposed by large-scale computational resources present a significant bottleneck. Furthermore, examples of large-scale computational discovery carried through experimental validation remain scarce, especially for materials with product applicability. In this paper, we demonstrate how this vision became reality by first combining state-of-the-art artificial intelligence (AI) models and traditional physics-based models on cloud high performance computing (HPC) resources to quickly navigate through more than 32 million candidates and predict around half a million potentially stable materials. Focusing on solid-state electrolytes for battery applications, our discovery pipeline further identified 18 promising candidates with new compositions and rediscovered a decade’s worth of collective knowledge in the field as a byproduct. By employing around one thousand virtual machines in the cloud, this process took less than 80 hours. We then synthesized and experimentally characterized the structures and conductivities of our top candidates, the Na x Li 3-x YCl 6 (0.5 ≤ x ≤ 2.5) series, demonstrating the potential of these compounds to serve as solid electrolytes. Additional candidate materials are currently under experimental investigation that could offer more examples of the computational discovery of new phases of Li- and Na-conducting solid electrolytes. We believe this unprecedented approach of synergistically integrating AI models and cloud HPC not only accelerates materials discovery but also showcases the potency of AI-guided experimentation in unlocking transformative scientific breakthroughs with real-world applications.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A Tidal Origin for a Three-body Resonance in Kepler-221

Over the course of the last two decades, traditional models of planet formation have been repeatedly challenged by the emerging census of extrasolar planets. Key among them is the orbital architecture problem: while standard models of orbital migration predict resonant orbits for short-period objects, most planets do not appear to lie in orbital resonances. Here, we show that the four-planet system Kepler-221, not previously recognized to have active orbital resonances, has a three-body commensurability relation unique within the Kepler sample. Using a suite of numerical experiments as well as a perturbative analysis, we demonstrate that this system likely began as a resonant chain and proceeded to undergo large-scale divergence away from resonance, under the action of tidal dissipation. Our results further indicate that obliquity tides, driven by a secular spin–orbit resonance and mutual inclination, are an excellent candidate for driving this orbital divergence, and that the high tidal luminosity may also explain the anomalous size of planet b, which lies within the Fulton radius gap.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1985

Observed and computed stellar line profiles - The roles played by partial redistribution, geometrical extent and expansion

Partial redistribution (PRD) radiative transfer is reviewed with emphasis on the complex interaction of observations and theoretical predictions of spectral line shapes. Although the physics of PRD was understood and formal solutions to the radiative transfer equation including PRD were published as early as 1962, more than a decade elapsed before the clear inconsistency between observed and theoretical profiles calculated with the restrictive assumption of complete redistribution stimulated the development and use of PRD semiempirical spectral analysis for the solar Lyman alpha, Ca II, and Mg II resonance lines. Work is summarized that led to 'realistic' plane parallel static chromospheric models for the sun and other late type stars, with emphasis on the determination of the temperature minimum at the base of the chromosphere and the physical basis for resonance line limb darkening, the brightness of the line wings, and the width of the emission features. Finally the various roles played by atmospheric extension and expansion (winds) in determining resonance line profile shapes are discussed, and the existing PRD calculations for late type stars are summarized.

Linsky, J. L.↗

NASA NTRS2000

Research Activities within NASA's Morphing Program

In the last decade, smart technologies have become important enabling technologies that cut across traditional boundaries in science and engineering. Here smart is defined as the ability to respond to a stimulus in a predictable and reproducible manner. While multiple successes have been achieved in the laboratory, we have yet to see the general applicability of smart technologies to actual aircraft and spacecraft. The NASA Morphing program is an attempt to couple research across a wide range of disciplines to integrate smart technologies into high payoff applications on aircraft and spacecraft. The program bridges research in several technical disciplines and combines the effort into applications that include active aerodynamic control, active aeroelastic control, and vehicle performance improvement. System studies are used to assess the highest-payoff program objectives, and specific research activities are defined to address the technologies required for development of smart aircraft and spacecraft. This paper will discuss the overall goals of NASA's Morphing program, highlight some of the recent research efforts and discuss the multidisciplinary studies that support that research and some of the challenges associated with bringing the smart technologies to real applications on flight vehicles.

McGowan, Anna-Maria R.↗

NASA NTRS2018

Management of Leshmaniases in the Era of Climate Change in Morocco

The proliferation of vector-borne diseases are predicted to increase in a changing climate and Leishmaniases, as a vector-borne diseases, are re-emerging diseases in several regions of the world. In Morocco, during the last decade, a sharp increase in cutaneous leishmaniases cases has been reported. Nevertheless, in Morocco, leishmaniases are a major public health problem, and little interest was given to climate change impacts on the distribution and spread of these diseases. As insect-borne diseases, the incidence and distribution of leishmaniases are influenced by environmental changes, but also by several socio-economic and cultural factors. From a biological point of view, environmental variables have effects on the survival of insect vectors and mammalian reservoirs, which, in turn, affects transmission. Here, we highlight the effects of climate change in Morocco and discuss its consequences on the epidemiology of leishmaniases to identify challenges and define targeted recommendations to fight this disease.

climate change↗

NASA NTRS2026

Updated global and regional trends of stratospheric ozone profiles

We present updated evaluation of stratospheric ozone profile trends in the 60° S–60°N latitude range using long-term ground-based and satellite climate data records, as well as simulations by chemistry-climate models. The trends are evaluated using the LOTUS (Long-term Ozone Trends and Uncertainties in the Stratosphere) regression model. Analyses of satellite data confirm the statistically significant positive ozone trends in the period 2000–2024 in the upper stratosphere of ~1–3% per decade, with larger trends at mid-latitudes compared to the tropics. The trends are slightly positive or close to zero in the middle stratosphere, and mostly negative, -1 to -2% per decade, in the lower stratosphere, but they are not statistically significant. The morphology and magnitude of ozone trends are similar to previous analyses (2000–2020 trends). Ozone trends in 2000–2024 predicted by chemistry-climate model simulations are in good agreement with combined satellite trends. In the upper stratosphere, models predict a slightly stronger ozone recovery than observations. In the lower stratosphere, both models and satellite observations report negative trends in the tropics, while modelled ozone trends are slightly positive at mid-latitudes. Ozone profile trends over several stations estimated from ground-based records capture the same overall vertical pattern of ozone trends as merged gridded satellite datasets. Analyses of regional ozone profile trends in 2003–2024 using merged satellite datasets confirmed the previous observations of a longitudinal structure in ozone trends in the NH mid-latitude stratosphere, with positive trends over Scandinavia and negative trends over Siberia. However, the magnitude of this dipole-like structure is reduced compared to previous analyses.

trends↗

NASA NTRS2024

Deducing Land-Atmosphere Coupling Regimes from SMAP Soil Moisture

In recent years, there has been a growing recognition of the significance of Land-Atmosphere (L-A) interactions and feedback mechanisms in understanding and predicting Earth’s water and energy cycles. Soil moisture plays a critical role in mediating the strength of L-A interactions and is important for understanding the complex and governing processes across this interface. This study aims to identify the significance of soil moisture in identifying L-A coupling strength within the Convective Triggering Potential (CTP) and Humidity Index (HI) framework. To address this, a consistent and reliable dataset of atmospheric profiles is created by merging CTP and HI using Triple Collocation (TC) with three reanalysis datasets. The merged CTP and HI product demonstrates enhanced performance globally as compared to the individual datasets when validated with radiosonde and satellite observations. This merged product of CTP and HI is then used to compare the L-A coupling strength based on Soil Moisture Active Passive Level 3 (SMAPL3) and SMAP Level 4 (SMAPL4) over two decades (2003-2022) where L-A coupling strength is defined as the persistence probability within the dry and wet coupling regimes. Results indicate that the persistency-based coupling strength is related to the ability of soil moisture to predict future atmospheric humidity and dry vs. wet coupling state. The coupling strength in SMAPL4 is consistently stronger than in SMAPL3 and is likely due to its reliance on a land surface model and reduced susceptibility to random noise. The difference in coupling strength based on the same CTP-HI underscores the importance of soil moisture data in estimating coupling strength within the CTP-HI framework. These findings lay the groundwork for understanding the role of L-A interactions and drought evolution due to soil moisture variations, by providing insight into the quantification of coupling strength and its role in drought monitoring and forecast efforts.

Land-atmosphere coupling↗

NASA NTRS2012

On the Probability of Occurrence of Extreme Space Weather Events

By virtue of their rarity, extreme space weather events, such as the Carrington event of 1859, are difficult to study, their rates of occurrence are difficult to estimate, and prediction of a specific future event is virtually impossible. Additionally, events may be extreme relative to one parameter but normal relative to others. In this study, we analyze several measures of the severity of space weather events (flare intensity, coronal mass ejection speeds, Dst, and greater than 30 MeV proton fluences as inferred from nitrate records) to estimate the probability of occurrence of extreme events. By showing that the frequency of occurrence scales as an inverse power of the severity of the event, and assuming that this relationship holds at higher magnitudes, we are able to estimate the probability that an event larger than some criteria will occur within a certain interval of time in the future. For example, the probability of another Carrington event (based on Dst less than - 850 nT) occurring within the next decade is approximately 12%. We also identify and address several limitations with this approach. In particular, we assume time stationarity, and thus, the effects of long-term space climate change are not considered. While this technique cannot be used to predict specific events, it may ultimately be useful for probabilistic forecasting.

Riley, Pete↗