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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Drivers of stability and transience in composition-functioning links during serial propagation of litter-decomposing microbial communities

ABSTRACT Biotic factors that influence the temporal stability of microbial community functioning are an emerging research focus for the control of natural and engineered systems. The discovery of common features within community ensembles that differ in functional stability over time is a starting point to explore biotic factors. We serially propagated a suite of soil microbial communities through five generations of 28-day microcosm incubations to examine microbial community compositional and functional stability during plant litter decomposition. Using dissolved organic carbon (DOC) abundance as a target function, we hypothesized that microbial diversity, compositional stability, and associated changes in interactions would explain the relative stability of the ecosystem function between generations. Communities with initially high DOC abundance tended to converge towards a “low DOC” phenotype within two generations, but across all microcosms, functional stability between generations was highly variable. By splitting communities into two cohorts based on their relative DOC functional stability, we found that compositional shifts, diversity, and interaction network complexity were associated with the stability of DOC abundance between generations. Further, our results showed that legacy effects were important in determining compositional and functional outcomes, and we identified taxa associated with high DOC abundance. In the context of litter decomposition, achieving functionally stable communities is required to utilize soil microbiomes to increase DOC abundance and long-term terrestrial DOC sequestration as one solution to reduce atmospheric carbon dioxide concentrations. Identifying factors that stabilize function for a community of interest may improve the success of microbiome engineering applications. IMPORTANCE Microbial community functioning can be highly dynamic over time. Identifying and understanding biotic factors that control functional stability is of significant interest for natural and engineered communities alike. Using plant litter–decomposing communities as a model system, this study examined the stability of ecosystem function over time following repeated community transfers. By identifying microbial community features that are associated with stable ecosystem functions, microbial communities can be manipulated in ways that promote the consistency and reliability of the desired function, improving outcomes and increasing the utility of microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1981

Time and frequency domain analysis of sampled data controllers via mixed operation equations

Specification of the mathematical equations required to define the dynamic response of a linear continuous plant, subject to sampled data control, is complicated by the fact that the digital components of the control system cannot be modeled via linear ordinary differential equations. This complication can be overcome by introducing two new mathematical operations; namely, the operation of zero order hold and digial delay. It is shown that by direct utilization of these operations, a set of linear mixed operation equations can be written and used to define the dynamic response characteristics of the controlled system. It also is shown how these linear mixed operation equations lead, in an automatable manner, directly to a set of finite difference equations which are in a format compatible with follow on time and frequency domain analysis methods.

Frisch, H. P.↗
NASA NTRS1984

Adaptive control: Myths and realities

It was found that all currently existing globally stable adaptive algorithms have three basic properties in common: positive realness of the error equation, square-integrability of the parameter adjustment law and, need for sufficient excitation for asymptotic parameter convergence. Of the three, the first property is of primary importance since it satisfies a sufficient condition for stabillity of the overall system, which is a baseline design objective. The second property has been instrumental in the proof of asymptotic error convergence to zero, while the third addresses the issue of parameter convergence. Positive-real error dynamics can be generated only if the relative degree (excess of poles over zeroes) of the process to be controlled is known exactly; this, in turn, implies perfect modeling. This and other assumptions, such as absence of nonminimum phase plant zeros on which the mathematical arguments are based, do not necessarily reflect properties of real systems. As a result, it is natural to inquire what happens to the designs under less than ideal assumptions. The issues arising from violation of the exact modeling assumption which is extremely restrictive in practice and impacts the most important system property, stability, are discussed.

Athans, M.↗
NASA NTRS1994

Simulation of a spatial, servo-hydraulic test facility for space structures

In this paper different control concepts for servo-hydraulic test facilities are derived using exact linearization techniques. Based on different linear and nonlinear models of the test table and the actuator dynamics several nonlinear controllers of different complexity are derived. The closed loop system performance of the controlled servo-hydraulic test facility is tested in various computer simulations using both, standard test signals and large test signals as system inputs. The simulation results turn out, that in case of standard input signals the test facility controller must include a linear test table mechanics model and a nonlinear servo-hydraulic actuator model. Additional simulations demonstrate the robustness of the control concept selected for standard test signals with respect to variations of plant parameters.

Leimbach, K.-D.↗
NASA NTRS1998

Algorithms for Efficient Computation of Transfer Functions for Large Order Flexible Systems

An efficient and robust computational scheme is given for the calculation of the frequency response function of a large order, flexible system implemented with a linear, time invariant control system. Advantage is taken of the highly structured sparsity of the system matrix of the plant based on a model of the structure using normal mode coordinates. The computational time per frequency point of the new computational scheme is a linear function of system size, a significant improvement over traditional, still-matrix techniques whose computational times per frequency point range from quadratic to cubic functions of system size. This permits the practical frequency domain analysis of systems of much larger order than by traditional, full-matrix techniques. Formulations are given for both open- and closed-loop systems. Numerical examples are presented showing the advantages of the present formulation over traditional approaches, both in speed and in accuracy. Using a model with 703 structural modes, the present method was up to two orders of magnitude faster than a traditional method. The present method generally showed good to excellent accuracy throughout the range of test frequencies, while traditional methods gave adequate accuracy for lower frequencies, but generally deteriorated in performance at higher frequencies with worst case errors being many orders of magnitude times the correct values.

Maghami, Peiman G.↗
NASA NTRS1997

Efficient Computation of Closed-loop Frequency Response for Large Order Flexible Systems

An efficient and robust computational scheme is given for the calculation of the frequency response function of a large order, flexible system implemented with a linear, time invariant control system. Advantage is taken of the highly structured sparsity of the system matrix of the plant based on a model of the structure using normal mode coordinates. The computational time per frequency point of the new computational scheme is a linear function of system size, a significant improvement over traditional, full-matrix techniques whose computational times per frequency point range from quadratic to cubic functions of system size. This permits the practical frequency domain analysis of systems of much larger order than by traditional, full-matrix techniques. Formulations are given for both open and closed loop loop systems. Numerical examples are presented showing the advantages of the present formulation over traditional approaches, both in speed and in accuracy. Using a model with 703 structural modes, a speed-up of almost two orders of magnitude was observed while accuracy improved by up to 5 decimal places.

Maghami, Peiman G.↗
DOE OSTI2022

Latent-Space Dynamics for Prediction and Fault Detection in Geothermal Power Plant Operations

This paper presents a latent-space dynamic neural network (LSDNN) model for the multi-step-ahead prediction and fault detection of a geothermal power plant’s operation. The model was trained to learn the dynamics of the power generation process from multivariate time-series data and the effects of exogenous variables, such as control adjustment and ambient temperature. In the LSDNN model, an encoder–decoder architecture was designed to capture cross-correlation among different measured variables. In addition, a latent space dynamic structure was proposed to propagate the dynamics in the latent space to enable prediction. The prediction power of the LSDNN was utilized for monitoring a geothermal power plant and detecting abnormal events. The model was integrated with principal component analysis (PCA)-based process monitoring techniques to develop a fault-detection procedure. The performance of the proposed LSDNN model and fault detection approach was demonstrated using field data collected from a geothermal power plant.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Trace Element Sampling and Partitioning Modeling to Estimate Wastewater Composition and Treatment Performance at Coal Generators

The coal combusted at coal-fired power plants (CFPPs) contains several trace elements that impact human heath if released to the environment. Effective combinations of air pollution control devices (APCDs) and water pollution control devices (WPCDs) are critical to reducing these impacts. This work sampled pulverized CFPPs owned and operated by Louisville Gas & Electricity – Kentucky Utilities (LGE-KU) during baseload and cycling conditions. Next, an open-source and easy-to-implement trace element partitioning model was developed using publicly available datasets, literature studies of trace element partitioning, and sampling data to estimate trace element partitioning in APCDs to the gas, liquid, and solid phases exiting CFPPs. These estimates of the liquid phase trace element concentration in FGD wastewater were then used to estimate trace element behavior in WPCDs and evaluate treated wastewater effluent concentrations for compliance with the Effluent Limitation Guidelines (ELG) for the Steam Electric Generating Sector. Finally, cost estimates were developed for established and emerging wastewater treatment trains to identify the most cost-effective approaches for ELG compliance.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Protein coating composition targets nanoparticles to leaf stomata and trichomes

Plant nanobiotechnology has the potential to revolutionize agriculture. However, the lack of effective methods to deliver nanoparticles (NPs) to the precise locations in plants where they are needed impedes these technological innovations. Here, model gold nanoparticles (AuNP) were coated with citrate, bovine serum albumin (BSA) as a protein control, or LM6-M, an antibody with an affinity for functional groups unique to stomata on leaf surfaces to deliver the AuNPs to stomata. One-month-old Vicia faba leaves were exposed via drop deposition to aqueous suspensions of LM6-M-coated AuNPs and allowed to air dry. After rinsing, Au distribution on the leaf surface was investigated by enhanced dark-field microscopy and X-ray fluorescence mapping. While citrate-coated AuNPs randomly covered the plant leaves, LM6M-AuNPs strongly adhered to the stomata and remained on the leaf surface after rinsing, and BSA-AuNPs specifically targeted trichome hairs. To the authors’ knowledge, this is the first report of active targeting of live leaf structures using NPs coated with molecular recognition molecules. Finally, this proof-of-concept study provides a strategy for future targeted nanopesticide delivery research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

A biosynthetic gene cluster for three post-chorismate pathways in Arabidopsis

Chorismate is a branch-point metabolite in the biosynthesis of aromatic amino acids, vitamins, antibiotics and various other aromatic products in bacteria, fungi and plants. Although 13 chorismate-utilizing enzymes have been identified in bacteria, only 6 have been described in plants, where an estimated 30% of all photosynthetically fixed carbon passes through chorismate. Here, in this study, we describe a biosynthetic gene cluster (BGC) consisting of five core genes, including two reductases, two methyltransferases and one glucosyltransferase. Genetic and biochemical evidence shows that these five enzymes collectively give rise to three biosynthetic pathways, each originating from chorismate: two parallel pathways produce a class of non-aromatic, isomeric compounds abundant in the roots of Arabidopsis thaliana, whereas the third pathway produces methylated and glucosylated chorismate derivatives that subsequently react non-enzymatically with glutathione. Genome analysis revealed that variants of this BGC are present in some but not all species in the Brassicaceae family. Taken together, our study uncovered a BGC, containing three chorismate-utilizing enzymes, that controls three distinct post-chorismate pathways in A. thaliana. This work not only advances our understanding of carbon flow in this model plant but also highlights that the biochemical complexity encoded by plant BGCs is greater than previously appreciated.

Peng, Meng [Ghent Univ. (Belgium); Flemish Institu↗
DOE OSTI2022

Control of Low-Inertia Power Systems

Electric power systems are undergoing an unprecedented transition from fossil fuel–based power plants to low-inertia systems that rely predominantly on power electronics and renewable energy resources. This article reviews the resulting control challenges and modeling fallacies, at both the device and system level, and focuses on novel aspects or classical concepts that need to be revised in light of the transition to low-inertia systems. To this end, we survey the literature on modeling of low-inertia systems, review research on the control of grid-connected power converters, and discuss the frequency dynamics of low-inertia systems. Moreover, we discuss system-level services from a control perspective. Overall, we conclude that the system-theoretic mindset is essential to bridge different research communities and understand the complex interactions of power electronics, electric machines, and their controls in large-scale low-inertia power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Diversity in Photoprotection and Energy Balancing in Terrestrial and Aquatic Phototrophs

The evolution of oxygenic photosynthesis enabled organisms to use sunlight as an energy source, allowing them to colonize new niches. At the same time, life (as we know it) places severe constraints on photosynthesis. For example, the initial reactions of photosynthesis involve highly energetic intermediates that, if not controlled, can generate highly toxic side products (especially reactive oxygen species, ROS), that can damage other essential components of the organisms it powers. Photosynthesis must therefore be tightly regulated to balance the need for efficient energy conversion with the necessity of avoiding photodamage (Gust D, Kramer D, Moore A, Moore T, Vermaas W, Mater Res Bull 33:383–389, 2008). A related constraint on photosynthesis is the need to precisely balance how much energy is stored in ATP and NADPH to precisely meet biochemical demands. If this balancing does not occur, the system will fail, leading to photodamage (Kramer DM, Evans JR, Plant Physiol 155:70–78, 2011). Consideration of these requirements is essential for efforts to improve the efficiency of photosynthesis by introducing CO 2 concentrating mechanisms, altering metabolism or biosynthetic pathways to shunt energy to alternative products (Kramer DM, Evans JR, Plant Physiol 155:70–78, 2011). These balancing processes must be extremely robust to contend with the rapid and unpredictable fluctuations in environmental conditions and metabolic demands that occur in nature. A large body of work has come from model systems, especially terrestrial higher plants and the green alga Chlamydomonas reinhardtii, leading to a model for the regulation of light reactions that involves 1) sensing of the pH gradient component of the thylakoid proton motive force (pmf), and 2) the redox state of the plastoquinone- and stromal pools. Over the short term, these sensors trigger regulation of light capture by altering the activity of ATP synthase leading to adjustments in lumen pH, which fine tunes light capture through nonphotochemical quenching (NPQ) and control of electron flow by adjusting the rate of PQH 2 oxidation at the b 6 f complex. Simultaneously, this system controls the balance of ATP/NADPH by adjusting electron flux to linear and cyclic electron flow pathways to balance ATP/NADPH. This integrated “pmf paradigm” model explains much of the existing data on plants and green algae, but may not extend to other diverse organisms. This review considers how advances in our understanding of photosynthesis over the past 7–8 years, particularly in the discoveries of diverse biochemical/biophysical mechanisms in aquatic photosynthetic species, affects the view of energy balance, including the shunting of electrons to O 2 through the flavodiiron proteins (FLV), the plastid terminal oxidase, the dissipation of electric field by ion movements, and the activation of alternative electron sinks. Furthermore, we will introduce the basic model that has been developed for higher plant chloroplasts, then contrast these with selected aquatic systems, focusing on how the differences impact the needs to re-balance both energy input and its partitioning into energy currencies.

Kanazawa, Atsuko↗
DOE OSTI2025

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗
NASA NTRS2012

Characteristics of Control Laws Tested on the Semi-Span Super-Sonic Transport (S4T) Wind-Tunnel Model

The Semi-Span Supersonic Transport (S4T) is an aeroelastically scaled wind-tunnel model built to test active controls concepts for large flexible supersonic aircraft in the transonic flight regime. It is one of several models constructed in the 1990's as part of the High Speed Research (HSR) Program. Control laws were developed for the S4T by M4 Engineering, Inc. and by Zona Technologies, Inc. under NASA Research Announcement (NRA) contracts. The model was tested in the NASA-Langley Transonic Dynamics Tunnel (TDT) four times from 2007 to 2010. The first two tests were primarily for plant identification. The third entry was used for testing control laws for Ride Quality Enhancement, Gust Load Alleviation, and Flutter Suppression. Whereas the third entry only tested FS subcritically, the fourth test demonstrated closed-loop operation above the open-loop flutter boundary. The results of the third entry are reported elsewhere. This paper reports on flutter suppression results from the fourth wind-tunnel test. Flutter suppression is seen as a way to provide stability margins while flying at transonic flight conditions without penalizing the primary supersonic cruise design condition. An account is given for how Controller Performance Evaluation (CPE) singular value plots were interpreted with regard to progressing open- or closed-loop to higher dynamic pressures during testing.

Christhilf, David M.↗
DOE OSTI2022

Dynamic genome evolution in a model fern

The large size and complexity of most fern genomes have hampered efforts to elucidate fundamental aspects of fern biology and land plant evolution through genome-enabled research. Here we present a chromosomal genome assembly and associated methylome, transcriptome and metabolome analyses for the model fern species Ceratopteris richardii. The assembly reveals a history of remarkably dynamic genome evolution including rapid changes in genome content and structure following the most recent whole-genome duplication approximately 60 million years ago. These changes include massive gene loss, rampant tandem duplications and multiple horizontal gene transfers from bacteria, contributing to the diversification of defence-related gene families. The insertion of transposable elements into introns has led to the large size of the Ceratopteris genome and to exceptionally long genes relative to other plants. Gene family analyses indicate that genes directing seed development were co-opted from those controlling the development of fern sporangia, providing insights into seed plant evolution. Our findings and annotated genome assembly extend the utility of Ceratopteris as a model for investigating and teaching plant biology.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

The dynamics and control of large flexible space structures, part 7

A preliminary Eulerian formulation of the in-plane dynamics of the proposed spacecraft control laboratory experiment configuration is undertaken when the mast is treated as a cantilever type beam and the reflector as a lumped mass at the end of the beam. Frequency and mode shapes are obtained for the open loop model of the beam system and the stability of closed loop control systems is analyzed by both frequency and time domain techniques. Environmental disturbances due to solar radiation pressure are incorporated into models of controlled large flexible orbiting platforms. Thermally induced deformations of simple beam and platform type structures are modelled and expressions developed for the disturbance torques resulting from the interaction of solar radiation pressure. Noise effects in the deterministic model of the hoop/column antenna system are found to cause a degradation in system performance. Appropriate changes in the ratio of plant noise to the measurement noise and/or changes in the control weighting matrix elements can improve transient and steady state performance.

Bainum, P. M.↗
NASA NTRS2019

How Does Water Delivery System Design Impact the Microbial Load of Salad Crops?

In a microgravity setting, such as the environment aboard the International Space Station (ISS), an ideal plant water delivery system is one that can grow edible crops with minimal resource consumption and minimal risk to crew members. There are also concerns associated with the ability to control fluid escape and biofilm formation resulting in potential dangers to systems, crops, or crewmembers. To identify an appropriate system, candidate systems were assembled and operated under simulated ISS environmental conditions (T,CO2,and RH) with red romaine lettuce (Lactuca sativa cultivar 'Outredgeous') as a model crop. Fluid reservoirs and randomly selected planting sites were sampled every seven days until maturity at which point edible plant biomass and root samples were also taken. Heterotrophic bacteria and fungi growth patterns throughout each planting cycle were determined by plate counts on appropriate agar media. The candidate systems were compared to a classic hydroponics system as a control and harvested crops were compared to controls as well as Veggie-grown and market produce. Plants harvested from candidate systems yielded lower average heterotrophic bacteria and fungi per gram of plant mass levels when compared to market and Veggie samples as well as those from the control system. Additional studies to evaluate the system sanitation regimen as well as testing additional crops should be considered to aid in the selection of an ideal system.

Curry, Aaron B.↗
NASA NTRS1993

A Data Base of Crop Nutrient Use, Water Use, and Carbon Dioxide Exchange in a 20 Square Meter Growth Chamber: Wheat as a Case Study - Part 1

A data set is given describing the daily nutrient uptake, gas exchange, environmental conditions, and carbon (C), and nutrient partitioning at harvest for the entire canopy and root system of a wheat crop (Triticum aestivum, cv. Yecora Rojo). The data were obtained from a 20 sq m stand of wheat plants grown from planting to maturity in a closed, controlled environment, and include daily nutrient uptake [macronutrients, nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), and sulfur (S); and micronutrients, iron (Fe), boron (B), manganese (Mn), zinc (Zn), copper (Cu), and molybdenum (Mo)], canopy carbon dioxide (CO2) exchange rates, and transpiration. Environmental factors such as relative humidity, air temperature, nutrient solution temperature, pH and electrical conductivity, and photoperiod were controlled in the chamber to specific set points. A detailed description of biomass yield for each of the 64 plant growth trays comprising the 20 sq m of growth area is also provided, and includes dry weights of grain, straw, chaff, and roots, along with the concentration of nutrients in different plant tissues and the percent carbohydrate, fat, and protein. To our knowledge, this information represents one of the most extensive data sets available for a canopy of wheat grown from seed to maturity under controlled environmental and nutritional conditions, and thus may provide useful information for model development and validation. A methods section is included to qualify any assumptions that might he required for the use of the data in plant growth models, along with a daily event calendar indicating when adjustments in set points and occasional equipment or sensor failures occurred.

Wheeler, Raymond M.↗