Programmable Transformations of DNA Origami Made of Small Modular Dynamic Units
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Chemistry↗
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Results for “unit dynamics”
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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Dynamic-RAM Data Storage Unit
Dynamic random-access-memory (RAM) data delay and storage unit developed to insure data received from satellite is stored and not lost when satellite is not within range of ground station. Stores 256K of serial data, with independent read and write capability.
Sturman, J. C.↗
Dynamic Torque Calibration Unit
Proposed dynamic torque calibration unit (DTCU) measures torque in rotary actuator components such as motors, bearings, gear trains, and flex couplings. Unique because designed specifically for testing components under low rates. Measures torque in device under test during controlled steady rotation or oscillation. Rotor oriented vertically, supported by upper angular-contact bearing and lower radial-contact bearing that floats axially to prevent thermal expansion from loading bearings. High-load capacity air bearing available to replace ball bearings when higher load capacity or reduction in rate noise required.
Agronin, Michael L.↗
Structured Neural Network Modeling for Developing Digital Twins Models of Hydropower Generation Units
Dynamic modeling is a key part in the development of digital twin (DT) for dynamic systems. This is true for hydropower systems, where whole system modeling including penstock, turbine and generators, etc is important in realizing actuate modeling for the real systems. On the other hand, in response to the large variations of the power demand due to increased penetration of renewables such as wind and solar, hydropower systems are now required to operate in a large power generation range. This situation triggers the nonlinear characteristics of the generation unit with respect to its models. As such, it is imperative to use data driven modeling such as neural networks to learn the nonlinear dynamics of the hydropower generation unit. To achieve this objective, this study constructs a modeling and learning algorithm integrated with multiple structured neural network models for the modeling of turbine shaft speed, penstock pressure, and generator power output based on the generator power control setpoint, field current, and field voltage. In addition, the study uses the hydropower data from Tacoma Public Utilities to train and validate the proposed neural network algorithm. The results have shown that this structured neural network modeling approach can learn the system dynamics effectively by using the real-time data collected from the hydropower system with the desired modeling results.
Wang, Hong↗
Analysis of shadowing effects on MIR photovoltaic and solar dynamic power systems
The NASA Lewis Research Center is currently working with RSC-Energia, the Russian Space Agency, and Allied Signal in developing a flight demonstration solar dynamic power system. This type of power system is dependent upon solar flux that is reflected and concentrated into a thermal storage system to provide the thermal energy input to a closed-cycle Brayton heat engine. The solar dynamic unit will be flown on the Russian Mir space station in anticipation of use on the International Space Station Alpha. By the time the power system is launched, the Mir will be a spatially complex configuration which will have, in addition to the three-gimbaled solar dynamic unit, eleven solar array wings that are either fixed or track the Sun along one axis and a variety or repositionable habitation and experiment modules. The proximity of arrays to modules creates a situation which makes it highly probable that there will be varying solar flux due to shadowing on the solar dynamic unit and some of the arrays throughout the orbit. Shadowing causes fluctuations in the power output from the arrays and the solar dynamic power system, thus reducing the energy capabilities of the spacecraft. An assessment of the capabilities of the power system under these conditions is an important part in influencing the design and operations of the spacecraft and predicting its energy performance. This paper describes the results obtained from using the Orbiting Spacecraft Shadowing Analysis Station program that was integrated into the Station Power Analysis for Capability Evaluation (SPACE) electrical power system computer program. OSSA allows one to consider the numerous complex factors for analyzing the shadowing effects on the electrical power system including the variety of spacecraft hardware geometric configurations, yearly and daily orbital variations in the vehicle attitude and orbital maneuvers (for communications coverage, payload pointing requirements and rendezvous/docking with other vehicles). The geometric models of the MIR with a solar dynamic power unit that were used in performing shadowing analyses are described. Also presented in this paper are results for individual orbits for several flight attitude cases which include assessments of the shadowing impacts upon the solar dynamic unit and the solar arrays. These cases depict typical MIR flight attitudes likely to have shadowing impact. Because of the time varying nature of the Mir orientation with respect to the Sun and the lack of knowledge of the precise timing of the attitude changes, strategies must be devised to assess and depict the shadowing impacts on power generation throughout the year. To address this, the best, nominal and worst impacts of shadowing considering a wide possible range of parameter changes for typical mission operation period are shown.
Fincannon, James↗
A High-Fidelity Molecular Model of the Cu(111) Repeating Unit
Dynamic processes at surfaces are central to heterogeneous catalysis, but their atomistic mechanism(s) can prove difficult to elucidate due to variations in material structure and the corresponding impact on reactivity. Moreover, disparities between reaction conditions and those employed for spectroscopic characterization at surfaces can inhibit detailed understanding of catalysis-relevant chemistries. Herein, we substantiate the so-called “cluster-surface” analogy by leveraging a low-valent tricopper architecture ( 1 ) as a model system for small molecule activation at Cu(111). Two reaction classes are explored: the adsorption of carbon monoxide (CO) and the dissociative adsorption of dihydrogen (H 2 ). These processes serve as an ideal testbed to compare the reactivity of a molecular cluster ( 1 ) to that of a heterogeneous surface, as both reactions have empirical data from measurements performed on crystalline Cu(111). Cluster 1 reversibly binds CO. Variable temperature NMR analysis with 13 CO reveals a favorable enthalpy but large negative entropy (−5.1 kcal × mol –1 and −22.9 cal × mol –1 × K –1 , respectively) for CO binding, affording a process that is marginally endergonic at room temperature (ΔG ads (298.15 K) = 1.7 ± 0.5 kcal × mol –1 ). Similarly, analogous to a Cu(111) surface, 1 is shown to oxidatively add (chemisorb) H 2 . Kinetic parameters were determined for this process and the activation enthalpy (8.4 ± 0.5 kcal × mol –1 ) closely mirrors that established for H 2 binding at the Cu(111) facet (6.0 to 12.4 kcal × mol –1 ). Together, these results showcase that a trinuclear cluster can reproduce the small molecule binding and activation energetics of a bulk crystalline surface, setting the stage for studying less-defined surface processes in an atomically precise molecular setting.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.
Rahimi, Stefan (ORCID:0000000331884462)↗
Probabilistic Risk Analysis (PRA) of a Mobile Offshore Drilling Unit (MODU) Dynamic Positioning System (DPS)
Probabilistic Risk Assessment (PRA) has been utilized by NASA in a variety of space oriented projects. It has served as one of the primary risk identification and ranking tools. Recent developments in the oil and gas industry have presented opportunities for NASA to lend their PRA expertise to both ongoing and developmental projects within the industry. As a result, NASA has entered into an agreement with Anadarko Petroleum Company (APC) to collaboratively develop PRAs for different aspects of the subsea drilling and completion process of well development. This paper documents how PRA was applied to estimate the probability that a Mobile Offshore Drilling Unit (MODU) equipped with a generically configured Dynamic Positioning System (DPS) loses location and needs to initiate an emergency disconnect. Since this project was in essence a pilot project, the PRA described in this paper is intended to be generic such that the vessel meets the general requirements of an International Maritime Organization (IMO) Maritime Safety Committee (MSC)/Circ. 645 Class 3 dynamically positioned vessel. The results of this analysis are not intended to be applied to any specific drilling vessel, although provisions were made to allow the analysis to be configured to a specific vessel if required.
Thigpen, Eric B.↗
The Dynamic Torque Calibration Unit: An instrument for the characterization of bearings used in gimbal applications
The Dynamic Torque Calibration Unit (DTCU), an instrument for the characterization of duplex ball bearing pairs used in gimbal applications, was designed and built. The design and operation of the unit are described. Preliminary data from the instrument are presented to illustrate the kinds of experiments that can be performed with the DTCU.
Jandura, Louise↗
The IDAES process modeling framework and model library—Flexibility for process simulation and optimization
Abstract Energy systems and manufacturing processes of the 21st century are becoming increasingly dynamic and interconnected, which require new capabilities to effectively model and optimize their design and operations. Such next generation computational tools must leverage state‐of‐the‐art techniques in optimization and be able to rapidly incorporate new advances. To address these requirements, we have developed the Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform, which builds on the strengths of both process simulators (model libraries) and algebraic modeling languages (advanced solvers). This paper specifically presents the IDAES Core Modeling Framework (IDAES‐CMF), along with a case study demonstrating the application of the framework to solve process optimization problems. Capabilities provided by this framework include a flexible, modifiable, open‐source platform for optimization of process flowsheets utilizing state‐of‐the‐art solvers and solution techniques, fully open and extensible libraries of dynamic unit operations models and thermophysical property models, and integrated support for superstructure‐based conceptual design and optimization under uncertainty.
42 ENGINEERING↗
Performance of graphite fiber-reinforced polyimide composites in self-aligning plain bearings to 315 C
A 50/50 (weight percent) composite of graphite fibers and polyimide was studied in self-aligning plain bearings oscillating + or - 15 degrees at 1 hz. The friction coefficient was 0.15 + or - 0.05 at 250 C, and 0.05 + or - 0.02 at 315 C. Best results were obtained with a molded composite liner with chopped graphite fibers randomly oriented in the composite. The specific wear rate is given. It was found that the dynamic unit load capacity was higher for a composite bushing (thin liner), than for a composite ball.
Sliney, H. E.↗
Reducing opioid use disorder and overdose deaths in the United States: A dynamic modeling analysis
Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; and (iii) recovery support for people in remission, which reduced deaths by reducing OUD. Increasing buprenorphine providers’ capacity to treat more people decreased fatal overdose, but only in the short term. Our analysis provides insight into the kinds of multifaceted approaches needed to save lives.
59 BASIC BIOLOGICAL SCIENCES↗
Status of computational fluid dynamics in the United States
CFD-related progress in U.S. aerospace industries and research institutions is evaluated with respect to methods employed, their applications, and the computer technologies employed in their implementation. Goals for subsonic CFD are primarily aimed at greater fuel efficiency; those of supersonic CFD involve the achievement of high sustained cruise efficiency. Transatmospheric/hypersonic vehicles are noted to have recently become important concerns for CFD efforts. Attention is given to aspects of discretization, Euler and Navier-Stokes general purpose codes, zonal equation methods, internal and external flows, and the impact of supercomputers and their networks in advancing the state-of-the-art.
Kutler, Paul↗
Ambulatory Healthcare Utilization in the United States: A System Dynamics Approach
Ambulatory health care needs within the United States are served by a wide range of hospitals, clinics, and private practices. The Emergency Department (ED) functions as an important point of supply for ambulatory healthcare services. Growth in our aging populations as well as changes stemming from broader healthcare reform are expected to continue trend in congestion and increasing demand for ED services. While congestion is, in part, a manifestation of unmatched demand, the state of the alignment between the demand for, and supply of, emergency department services affects quality of care and profitability. The central focus of this research is to provide an explanation of the salient factors at play within the dynamic demand-supply tensions within which ambulatory care is provided within an Emergency Department. A System Dynamics (SO) simulation model is used to capture the complexities among the intricate balance and conditional effects at play within the demand-supply emergency department environment. Conceptual clarification of the forces driving the elements within the system , quantifying these elements, and empirically capturing the interaction among these elements provides actionable knowledge for operational and strategic decision-making.
Diaz, Rafael↗
Global Ecosystem Dynamics Investigation (GEDI) Structural Verification Unit (SVU) Vibration Test
This presentation describes the vibration test campaign of the Structural Verification Unit for the Global Ecosystem Dynamics Investigation (GEDI) mission The Structural Verification Unit test campaign served multiple purposes including the qualification of the instrument primary structure, verification of the structure's stiffness, Aperture Control Mechanism assembly level verification, and validation of the control approach for protoflight instrument vibration testing. Testing included three axes of sine burst, random, and sine vibration excitation. This test sequence required a high number of response instrumentation sensors that included tri-axial accelerometers and tri-axial force gauges. Multiple response limiting methods that included acceleration, force, and moment measurements were used to ensure the safety of the flight hardware. The lessons and specific test details learned on the structural verification unit test campaign will reduce test risks for the upcoming instrument-level vibration tests.
Structural Verification Unit↗
Computational fluid dynamics research at the United Technologies Research Center requiring supercomputers
An overview of research activities at the United Technologies Research Center (UTRC) in the area of Computational Fluid Dynamics (CFD) is presented. The requirement and use of various levels of computers, including supercomputers, for the CFD activities is described. Examples of CFD directed toward applications to helicopters, turbomachinery, heat exchangers, and the National Aerospace Plane are included. Helicopter rotor codes for the prediction of rotor and fuselage flow fields and airloads were developed with emphasis on rotor wake modeling. Airflow and airload predictions and comparisons with experimental data are presented. Examples are presented of recent parabolized Navier-Stokes and full Navier-Stokes solutions for hypersonic shock-wave/boundary layer interaction, and hydrogen/air supersonic combustion. In addition, other examples of CFD efforts in turbomachinery Navier-Stokes methodology and separated flow modeling are presented. A brief discussion of the 3-tier scientific computing environment is also presented, in which the researcher has access to workstations, mid-size computers, and supercomputers.
Landgrebe, Anton J.↗
Exploiting electricity market dynamics using flexible electrolysis units for retrofitting methanol synthesis
Here we investigate the economic viability of integrating flexible electrolysis units to produce hydrogen in methanol synthesis processes. Specifically, we investigate whether this approach can help reduce methanol production costs by strategically exploiting dynamics of electricity markets. Our study integrates high-fidelity process simulations, optimization tools, and microkinetic modeling (informed by density functional theory) to conduct detailed techno-economic analyses and to compare performance against traditional processes that use hydrogen produced via steam-methane reforming (SMR). We also use this approach to estimate the levelized cost of hydrogen (LCOH) as a function of time-varying electricity prices (from day-ahead and real-time prices) and of key techno-economic parameters. Our results show that the proposed electrification framework is cost-competitive under certain electricity market conditions. Specifically, we find that, when the electrolysis system is operated in flexible mode (and can respond to dynamics of electricity markets), the associated electricity cost nearly collapses to zero. Conversely, when the unit is not flexible (and cannot respond to markets), the electricity cost comprises 60% of the total cost. Our results also reveal that the LCOH of the flexible electrolysis system participating in real-time electricity markets is 31% lower than the LCOH obtained from SMR. Overall, this indicates that exploiting the dynamics of electricity markets can make hydrogen production cost-competitive and this can lead to viable alternatives to electrify methanol production and other hydrogen-based processes.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
High-Performance Semiempirical Excited-State Molecular Dynamics Powered by Graphics Processing Units
Here, this Letter introduces excited-state molecular dynamics in PYSEQM, a GPU-accelerated semiempirical quantum chemistry engine implemented in PyTorch. The new module enables Born–Oppenheimer molecular dynamics (BOMD) using configuration-interaction singles and random phase approximation for excited states, allowing long trajectories and large statistical ensembles to be simulated efficiently on a single GPU. We also implement an extended Lagrangian excited-state BOMD (XL-ESMD) scheme that propagates auxiliary electronic variables, enabling relaxed ground and excited-state convergence thresholds without compromising energy conservation. The excited-state BOMD implementation scales smoothly from small chromophores to a nearly 900-atom dendrimer (taking 6.5 s per MD step). PYSEQM also supports batched execution, allowing many geometries or trajectories to be evaluated in a single GPU launch, substantially increasing throughput and making ensemble-based protocols routine. As a demonstration, we compute absorption, emission, and infrared spectra from trajectories propagated on the ground and first excited states. The XL-ESMD scheme yields identical spectra at significantly lower computational cost, establishing the role of extended Lagrangian based dynamics for efficient excited-state BOMD simulations. Beyond raw performance, PYSEQM’s PyTorch foundation provides automatic differentiation for forces, efficient GPU batching, and seamless interfacing with machine learning models. These capabilities position PYSEQM as a practical platform for machine learning-augmented excited-state dynamics and lay the foundation for future data-driven nonadiabatic excited-state dynamics modeling of ultrafast spectroscopic probes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗