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Simulating compound flooding (CF) at the river-ocean interface within large-scale Earth System Models (ESMs) presents significant challenges due to complex interactions between river discharge, storm surge, and tides. This study assesses the comparative advantages of physics-informed and data-driven machine learning (ML) approaches for enhancing local ESM performance. We systematically compare data-driven neural network models (i.e., CNNs, U-Net, Long Short-Term Memory (LSTM), Gated Recurrent Unit), and physics-informed neural network (PINN) models, including vanilla PINN and a finite-difference-based PINN (FD-PINN). Specifically, FD-PINN is introduced to enhance computational efficiency, accelerating vanilla PINNs by ∼6.5 times while improving accuracy. To enhance data-driven model training, a new data-generation approach is developed to sample historical fluvial and coastal flood events, which ensures a robust data set for extreme event prediction. The models are evaluated using a realistic one-dimensional river domain extracted from an ESM's river mesh and the Hurricane Irene event as an independent test case. Results show that FD-PINN achieves accurate predictions with significantly reduced computational costs relative to vanilla PINNs. Among data-driven models, the best overall performance is achieved by a CNN-LSTM hybrid, which balances accuracy and efficiency. While a fully connected CNN (CNN-FC) provides the best accuracy, it incurs high computational cost. Architectures lacking strong temporal modeling tend to underperform on unseen events. These findings highlight the importance of sequence-aware designs for robust generalization. This study reveals the trade-offs between physics-informed and data-driven models and proposes an adaptive hybrid framework for integrating ML into ESMs to enhance local flood simulations.
Infrared and visible HCMM data were used to examine the potential application of these data to define initial and boundary conditions for mesoscale numerical models. Various boundary layer models were used to calculate the distribution of the surface heat flux, specific humidity depression (the difference between the specific humidity in the air at approxmately the 10 m level and the specific humidity at the ground), and the eddy vicosity in a 72 km by 72 km area centered about St. Louis, Missouri. Various aspects of the implications of the results on the meteorology of St. Louis are discussed. Overall, the results indicated that a reasonable estimate of the surface heat flux, urban albedo, ground temperature, and specific humidity depression can be obtained using HCMM satellite data. Values of the ground-specific humidity can be obtained if the distribution of the air-specific humidity is available. More research is required in estimating the absolute magnitude of the specific humidity depression because calculations may be sensitive to model parameters.
To strengthen Malawi's national electricity grid and to enhance reliability, the government of Malawi and the Electricity Supply Corporation of Malawi are partnering with the Global Alliance for People and Planet to develop a 20-megawatt/30-megawatt-hour battery energy storage system at Kanengo, Malawi, expected to come online in 2026. In parallel, the Global Energy Alliance for People and Planet and the National Laboratory of the Rockies implemented a comprehensive technical capacity-building program to equip the Electricity Supply Corporation of Malawi, the Malawi Energy Regulatory Authority, and the Malawi University of Business and Applied Sciences with the expertise needed to plan, regulate, and operate advanced storage systems.
This study models the transition of CO 2 -enhanced oil recovery (CO 2 -EOR) fields to dedicated carbon storage using a generalized reservoir model informed by real field data, SACROC. Through scenario-based simulations, the work evaluates how reservoir depletion levels, boundary conditions, fluid properties, and domain size affect pressure buildup, CO 2 plume migration, and long-term containment performance. The results inform practices for repurposing oil fields into reliable CO 2 storage sites.
This is a three-paper dissertation that responds to a call for empirical research on stakeholder influence in the implementation of evaluation recommendations. The literature is consistent but mostly theoretical: stakeholder participation should positively influence and increase the probability of implementation (see e.g., Christie, 2011; Cousins and Earl, 1992); Fetterman, 2004). In response, I use two Goddard Space Flight Center engineering technical training and development programs to build a causal pathway argument supporting my proposition that stakeholder influence in the logic modeling process impacts organizational decision-making and change. I first introduce the logic modeling process as a tool to involve stakeholders in program and evaluation design (paper 1), then use the data collection process to implement the collaboratively constructed logic model outcomes (paper 2), and finally, I triangulate the data using the Toal (2009) Evaluation Involvement Scale (paper 3). I do this to “increase the validity of the findings” (Noble & Heale, 2019, p. 67) and to garner potential mechanisms. I found that stakeholder participation in the logic modeling process positively influenced the use of data to inform recommendations which in turn positively influenced implementation of evaluation recommendations. I identified the process itself as the mechanism and the key decision points as links or influencers. Potential factors included power and interest (measured by role) and time-on-job.
The use of the case method in teaching various technical communication skills is described. Features of the method considered include: solving communication problems, identifying an audience, planning written communications, presenting written communications, and using visual aids.
Large errors in numerical weather prediction are often associated with explosive cyclogenesis. Most studes focus on the under-forecasting error, i.e. cases of rapidly developing cyclones which are poorly predicted in numerical models. However, the over-forecasting error (i.e., to predict an explosively developing cyclone which does not occur in reality) is a very common error that severely impacts the forecasting skill of all models and may also present economic costs if associated with operational forecasting. Unnecessary precautions taken by marine activities can result in severe economic loss. Moreover, frequent occurrence of over-forecasting can undermine the reliance on operational weather forecasting. Therefore, it is important to understand and reduce the prdctions of extreme weather associated with explosive cyclones which do not actually develop. In this study we choose a very prominent case of over-forecasting error in the northwestern Pacific. A 960 hPa cyclone develops in less than 24 hour in the 5-day forecast, with a deepening rate of about 30 hPa in one day. The cyclone is not versed in the analyses and is thus a case of severe over-forecasting. By assimilating AIRS data, the error is largely eliminated. By following the propagation of the anomaly that generates the spurious cyclone, it is found that a small mid-tropospheric geopotential height negative anomaly over the northern part of the Indian subcontinent in the initial conditions, propagates westward, is amplified by orography, and generates a very intense jet streak in the subtropical jet stream, with consequent explosive cyclogenesis over the Pacific. The AIRS assimilation eliminates this anomaly that may have been caused by erroneous upper-air data, and represents the jet stream more correctly. The energy associated with the jet is distributed over a much broader area and as a consequence a multiple, but much more moderate cyclogenesis is observed.
A comparison of 1262 cases of coincident ozone profiles derived from 666 Umkehrs at 17 different stations and 901 SAGE 2 profiles within 1000 km and 12 hours between October 1984 and April 1989 indicates the following layer percentage differences with 2-sigma error bars: layer three 14.6 plus/minus 3.3 percent, layer four 17.6 plus/minus 1.1 percent, layer five -1.3 plus/minus 0.5 percent, layer six -5.7 plus/minus 0.7 percent, layer seven -1.0 plus/minus 0.7 percent, layer eight 4.2 plus/minus 0.7 percent, and layer nine 6.8 plus/minus 1.2 percent. Comparing SAGE 2-Umkehr differences to SAGE 1 version 5.5-Umkehr differences shows SAGE 2 higher than or equal to SAGE 1 relative to Umkehr in all layers except layer three. Adjustment for this bias would produce trends derived from SAGE 2-SAGE 1 differences and Umkehr observations in the 1980s more nearly equal to each other in layers six, seven, and eight. A possible explanation of these differences is a systematic shift in the reference altitude between SAGE 1 and SAGE 2, but there is no independent evidence of this. While the shape of the vertical profile of differences at 17 individual Umkehr stations (mostly in mid-latitudes) is generally consistent at all stations except at Poker Flat, Seoul, and Lauder, significant variation does exists among the stations. The profile of mean difference is similar to previously observed differences between Umkehr and both SAGE 2 and SBUV and also to an eigenvector analysis, but with site-dependent amplitude discrepancies. Because of the close correspondence of stratospheric aerosol optical depth at the SAGE 2-measured 0.525 micron wavelength and the extrapolated 0.32 Umkehr wavelength determined in this study, we use the 0.525 micron data to determine the aerosol effect of Umkehr profiles. The aerosol errors to the Umkehr ozone amounts in percent ozone amount per 0.01 stratospheric aerosol optical depth range from plus 2 percent in layer six to minus 3 percent in layer nine. These results agree with previous theoretical and empirical studies within their respective error bounds in layers nine, eight, and five. The result in layer six differs significantly from previous works. In view of the fact that SAGE 2 and Umkehr produce different ozone retrievals in layers eight and nine and because the intra-layer correlation of SAGE 2 ozone and aerosol in layers eight and nine in non-zero, one must exercise some caution in attributing the entire SAGE 2-Umkehr differences in the upper layers to an aerosol effect.
Modeling for space vehicle design needs to consider: 1) The Human Factor; and 2) The Mission Factor. The Test Case of a crew resource model in this viewgraph presentation includes: 1) The Problem; 2) Crew Accomodations Resource Model; and 3) Conculsions on the model's utility for working the problem. The presentation uses the Crew Accomodations Resource Model to determine the mass and volume of supplies and equipment for a hypothetical manned Mars mission.
A screening-level techno-economic analysis of a passive limestone looping direct air capture system is presented. The base case examined in this report does not represent an optimized system and makes many simplifying assumptions due to the nascence of the technology and lack of publicly available information. The base case serves as a reference for detailed and informative sensitivity analyses. This initial study (1) reveals that improving reaction rate and tray configuration can potentially significantly reduce cost, and (2) indicates that LL has the potential to be cost competitive with other DAC technologies.
Recent neuropsychological studies demonstrate that cognitive dysfunction is a common symptom in patients with multiple sclerosis. In many cases the presence of cognitive impairment affects the patient's daily activities to a greater extent than would be found due to their physical disability alone. Cognitive dysfunction can have a significant impact on the quality of life of both the patient and that of their primary caregiver. Two cognitively impaired male MS patients were given a visual discrimination task before and after a one hour cooling period. The subjects were presented a series of either red or blue circles or triangles. One of these combinations, or one fourth of the stimuli, was designated as the "target" presentation. EEG was recorded from 20 scalp electrodes using a Tracor Northern 7500 EEG/ERP system. Oral and ear temperatures were obtained and recorded manually every five minutes during the one hour cooling period. The EEG ERP signatures from each series of stimuli were analyzed in the energy density domain to determine the locus of neural activity at each EEG sampling time. The first subject's ear temperature did not decrease during the cooling period. It was actually elevated approximately 0.05 C by the end of the cooling period compared to his mean of control period value. In turn, Subject One's discrimination performance and cortical energy remained essentially the same after body cooling. In contrast, Subject Two's ear temperature decreased approx. 0.8 C during his cooling period. Subject Two's ERROR score decreased from 12 during the precooling control period to 2 after cooling. His ENERGY value increased approximately 300%, from a precooling value of approximately 200 to a postcooling value of nearly 600. These findings might be interpreted by the following three-part hypothesis: (1) the general cognitive impairment of MS patients may be a result of low or unfocused metabolic energy conversion in the cortex; (2) such differences show up most strongly in reduced energy in the occipital region during the initial processing of the precooling period visual stimulus which may indicate impaired early visual processing; and (3) increased postcooling activation in the le ft angular gyrus may result in enhanced higher-level reasoning related to processing visual task information. By this hypothesis the superior performance of Subject Two following body cooling may be a result of increased neural activation in his early visual recognition and processing centers.
Arc jet testing is used to simulate entry to test thermal protection materials. This paper discusses the usefulness of arc jet testing for 3 cases. Case 1 is MSL and PICA, Case 2 is Advanced TUFROC, and Case 3 is conformable ablators.
Current Ada language implementations and runtime environments are immature, unproven and are a key risk area for real-time embedded computer system (ECS). A test-case environment is provided in which the concerns of the real-time, ECS community are addressed. A priority driven executive is selected to be implemented in the Ada programming language. The model selected is representative of real-time executives tailored for embedded systems used missile, spacecraft, and avionics applications. An Ada-based design methodology is utilized, and two designs are considered. The first of these designs requires the use of vendor supplied runtime and tasking support. An alternative high-level design is also considered for an implementation requiring no vendor supplied runtime or tasking support. The former approach is carried through to implementation.
The vibrational frequencies and infrared intensities of naphthalene neutral and cation are studied at the self-consistent-field (SCF), second-order Moller-Plesset (MP2), and density functional theory (DFT) levels using a variety of one-particle basis sets. Very accurate frequencies can be obtained at the DFT level in conjunction with large basis sets if they are scaled with two factors, one for the C-H stretches and a second for all other modes. We also find remarkably good agreement at the B3LYP/4-31G level using only one scale factor. Unlike the neutral PAHs where all methods do reasonably well for the intensities, only the DFT results are accurate for the PAH cations. The failure of the SCF and MP2 methods is caused by symmetry breaking and an inability to describe charge delocalization. We present several interesting cases of symmetry breaking in this study. An assessment is made as to whether an ensemble of PAH neutrals or cations could account for the unidentified infrared bands observed in many astronomical sources.
Software development projects face numerous challenges that threaten their successful completion. Whether it is not enough money, too little time, or a case of "requirements creep" that has turned into a full sprint, projects must meet these challenges or face possible disastrous consequences. A robust, yet flexible process model can provide a mechanism through which software development teams can meet these challenges head on and win. This article describes how the spiral model has been successfully tailored to a specific project and relates some notable results to date.
This study investigates the effects of urbanization, specifically land use change and anthropogenic emissions (AE), on convection, lightning, and surface precipitation for a case of summertime sea‐breeze convection observed over the Houston metropolitan area. The unique capabilities of the NASA‐Unified Weather Research and Forecasting model allows us to conduct a series of sensitivity experiments with complex configurations, in particular including multi‐year land model spin‐up simulations, treatment of aerosols and their precursors, and explicit cloud charging and lightning. The simulation results show that urban land use primarily alters the temporal evolution of convection, lightning, and surface precipitation, leading to late afternoon thunderstorm development. The decrease in latent heat flux from the land surface caused by urbanization weakens convection in the early afternoon, while a condition suitable for convection development is maintained in the late afternoon due to less stabilization of the lower troposphere by the weaker convection development and high sensible heat flux from the surface. On the other hand, anthropogenic aerosols directly enhance convection, lightning, and surface precipitation by increasing convective updrafts due to the aerosol‐induced convective invigoration. The combined effects of urban land use and AE lead to even stronger thunderstorms in the late afternoon, mostly consistent with observations. These results indicate that urbanization increases the probability of late afternoon thunderstorms over the Houston area during the summer season. Advanced weather forecasting models that incorporate these urbanization effects might support sustainable urban planning to better mitigate the impacts of urbanization on local weather and public safety.
The Galileo spacecraft may be targeted for a close flyby of an asteroid on its way to an encounter with Jupiter. An orbit determination accuracy analysis was carried out for the case of the asteroid 29 Amphitrite based on the use of radio metric and optical data types. Prior to encounter, the uncertainty in the asteroid's position, based on astrometric observations from earth, amounts to several hundred kilometers. This ephemeris uncertainty constitutes the dominant error in the determination of the spacecraft orbit with respect to Amphitrite. It is shown that the spacecraft-asteroid relative position can be improved by imaging asteroid-star pairs with the Galileo charge-coupled device (CCD) camera, enabling an accurate flyby of the asteroid. The main benefit of optical navigation is to enable the instrument pointing updates necessary for closeup viewing of the asteroid. A discussion of the evolution of the target error ellipse parameters as a function of data coverage and various combinations of radiometric and optical data types is also presented.