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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Leveraging System Dynamics to Predict the Commercialization Success of Emerging Energy Technologies: Lessons from Wind Energy

The United States urgently needs to tackle the climate crisis while enhancing energy security and resiliency. The complexity of the U.S. energy system, with its interconnected elements, makes predicting future states challenging, especially with the introduction of novel energy systems like wind, solar, clean hydrogen, and advanced nuclear technologies. Modern systems engineering methods and tools can provide deeper insights into these dynamics and future behaviors. This research aims to develop a comprehensive model that captures the main elements and behaviors of new energy technologies within the existing energy system. We hypothesized that the market uptake of novel energy systems is influenced by multiple diverse factors, such as technological learning, availability of resources, and economic incentives; examined the history of electricity generation using land-based wind technologies; and developed a system dynamics model to investigate the relationships between capacity growth and influencing factors, both internal and external. The developed model yielded outcomes that confirmed the hypothesized dynamics of wind energy system diffusion through a quantitative comparison of installed capacity and highlighted the significant influence of resource availability, federal incentives (production tax credits), and technological learning on capacity growth and cost reduction. This research aims to support informed decision-making for investments in novel energy systems and aid in developing effective policies for technology deployment.

17 WIND ENERGY↗
DOE OSTI2025

Comparison of GOES16 Data with the TRACER-ESCAPE Field Campaign Dataset for Convection Characterization: A Selection of Case Studies and Lessons Learnt

Convective updrafts are one of the main characteristics of convective clouds, responsible for the convective mass flux and the redistribution of energy and condensate in the atmosphere. During the early stages of their lifecycle, convective clouds experience rapid cloud-top ascent manifested by a decrease in the geostationary IR brightness temperature (𝑇⁢𝐵 𝐼⁢𝑅 ). Under the assumption that the convective cloud top behaves like a black body, the ascent rate of the convective cloud top can be estimated as ($\frac{∂𝑇⁢𝐵_{𝐼⁢𝑅}}{∂𝑡}$), and it can be used to infer the near cloud-top convective updraft. The temporal resolution of the geostationary IR measurements and non-uniform beam-filling effects can influence the convective updraft estimation. However, the main shortcoming until today was the lack of independent verification of the strength of the convective updraft. Here, Doppler radar observations from the ESCAPE and TRACER field experiments provide independent estimates of the convective updraft velocity at higher spatiotemporal resolution throughout the convective core column and can be used to evaluate the updraft velocity estimates from the IR cooling rate for limited samples. Isolated convective cells were tracked with dedicated radar (RHIs and PPIs) scans throughout their lifecycle. Radial Doppler velocity measurements near the convective cloud top are used to provide estimates of convective updrafts. These data are compared with the geostationary IR and VIS channels (from the GOES satellite) to characterize the convection evolution and lifecycle based on cloud-top cooling rates.

TRACER/ESCAPE field campaign↗
DOE OSTI2025

Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling

AI models are criticized as being black boxes, potentially subjecting climate science to greater uncertainty. Explainable artificial intelligence (XAI) has been proposed to probe AI models and increase trust. In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. Dynamical models are complex but have gained trust because their successes and failures can sometimes be attributed to specific components or sub-models, such as when model bias is explained by pointing to a particular parameterization. We propose three types of understanding as a basis to evaluate trust in dynamical and AI models alike: (1) instrumental understanding, which is obtained when a model has passed a functional test; (2) statistical understanding, obtained when researchers can make sense of the modeling results using statistical techniques to identify input–output relationships; and (3) component-level understanding, which refers to modelers' ability to point to specific model components or parts in the model architecture as the culprit for erratic model behaviors or as the crucial reason why the model functions well. We demonstrate how component-level understanding has been sought and achieved via climate model intercomparison projects over the past several decades. Such component-level understanding routinely leads to model improvements and may also serve as a template for thinking about AI-driven climate science. Currently, XAI methods can help explain the behaviors of AI models by focusing on the mapping between input and output, thereby increasing the statistical understanding of AI models. Yet, to further increase our understanding of AI models, we will have to build AI models that have interpretable components amenable to component-level understanding. We give recent examples from the AI climate science literature to highlight some recent, albeit limited, successes in achieving component-level understanding and thereby explaining model behavior. The merit of such interpretable AI models is that they serve as a stronger basis for trust in climate modeling and, by extension, downstream uses of climate model data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1971

Lessons learned from a decade of international space cooperation.

A case history of the Alouette/ISIS series is presented, giving attention to aspects of U.S.-Canadian cooperation in this program. The project is only one example of a broad network of international cooperative relationships established by NASA over the past decade. Participation by other countries in important space science and applications projects is not limited to those providing flight hardware or conducting flight observations. Much valuable work is done on the ground, ranging from analysis in the laboratories of samples returned from the moon to correlated ground-based reception and analysis of radio beacon signals from satellites. It was found that cooperation is more likely to proceed smoothly and produce beneficial results if it is focused on projects that are clearly defined and agreed on in advance.

Barnes, R. J. H.↗
NASA NTRS1980

Mission management - Lessons learned from early Spacelab missions

The concept and the responsibilities of a mission manager approach are reviewed, and some of the associated problems in implementing Spacelab mission are discussed. Consideration is given to program control, science management, integrated payload mission planning, and integration requirements. Payload specialist training, payload and launch site integration, payload flight/mission operations, and postmission activities are outlined.

Craft, H. G., Jr.↗
NASA NTRS1980

Differentiation of crusts and cores of the terrestrial planets - Lessons for the early earth

The extent and mechanisms of global differentiation and the early thermal and tectonic histories of the terrestrial planets are surveyed in order to provide constraints on the first billion years of earth history. Indirect and direct seismic evidence for crusts on the moon, Mars and Venus is presented, and it is pointed out that substantial portions of these crusts have been in place since the cessation of heavy bombardment of the inner solar system four billion years ago. Evidence for sizable cores on Mars and Mercury and a small core on the moon is also discussed, and the heat involved in core formation is pointed out. Examination of the volcanic and tectonic histories of planets lacking plate tectonics indicates that core formation was not closely linked to crust formation on the moon or Mars, with chemical differentiation restricted to shallow regions, and was much more extensive on Mercury. Extension of these considerations to the earth results in a model of a hot and vigorously convecting mantle with an easily deformable crust immediately following core formation, and the gradual development of a lithosphere and plates.

Solomon, S. C.↗
NASA NTRS1981

The OSS-1 mission - Lessons learned in developing and integrating experiments

Experience gained in the development and integration of experiments for the OSS-1 payload to be carried on board the Space Shuttle for the characterization of the effects of the STS environment on future scientific missions is related. Following a review of mission objectives, including the demonstration of Shuttle research capabilities and the evaluation of new technology, the experiments and mission operations to be performed are outlined, and mission support requirements are indicated. The conduct of mission management by the Goddard Space Flight Center, which required interfacing with a large number of other agencies, centers, and investigators and contractors and an enormous amount of formal documentation, is then examined, with consideration given to the management of mechanical, electrical, and thermal systems development mock-up construction, EMI/EMC and acoustic testing, the formation of an integration and test team, and trade-offs between cost, schedule and performance. It is concluded that although work still remains to be done, significant progress has been made in ensuring that the STS is a viable system for space exploration.

Kissin, K.↗
NASA NTRS1981

Lessons from NASA

Particular requirements related to the design and the operation of spacecraft have forced NASA to take a reliability approach that differs somewhat from that used in many other applications. NASA has found that some of the traditional tools of reliability engineering, such as life testing, reliability demonstration testing, maintainability analysis, and direct failure analysis, are impractical for spacecraft. In place of a statistical approach, the space agency uses an engineering approach to mission reliability. Reliability is to be obtained with the aid of three different approaches, including the application of effective design principles, the control and screening of all parts, and the testing of the entire spacecraft or its prototype for predicted capabilities. Attention is given to failure-mode analysis, the enhancement of Voyager reliability by autonomous operation, the redundancy in Shuttle design, the weeding out of bad hardware, and the preference for off-the-shelf devices.

Williams, W. C.↗