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An overview of Observing System Simulation Experiments (OSSEs) will be given, with focus on calibration and validation of OSSE frameworks. Pitfalls and practice will be discussed, including observation error characteristics, incestuousness, and experimental design. The potential use of OSSEs for investigation of the behaviour of data assimilation systems will be explored, including some results from experiments using the NASAGMAO OSSE.
An overview of Observing System Simulation Experiments (OSSEs) will be given, with focus on calibration and validation of OSSE frameworks. Pitfalls and practice will be discussed, including observation error characteristics, incestuousness, and experimental design. The potential use of OSSEs for investigation of the behaviour of data assimilation systems will be explored, including some results from experiments using the NASAGMAO OSSE.
Tremendous strides have been made in the recent years to digitally represent human beings in computer simulation models ranging from assembly plant maintenance operations to occupants getting in and out of vehicles to action movie scenarios. While some of these tools are being actively pursued by the engineering communities, there is still a lot of work that remains to be done for the newly planned planetary exploration missions. For example, certain unique and several common challenges are seen in developing computer generated suited human models for designing the next generation space vehicle. The purpose of this presentation is to discuss NASA s potential needs for better human models and to show also many of the inherent yet not too obvious pitfalls that still are left unresolved in this new arena of digital human modeling. As part of NASA s Habitability and Human Factors Branch, the Anthropometry and Biomechanics Facility has been engaged in studying the various facets of computer generated human physical performance models; for instance, it has been engaged in utilizing three-dimensional laser scan data along with three dimensional video based motion and reach data to gather suited anthropometric and shape and size information that are not available yet in the form of computer mannequins. Our goal is to bring in new approaches to deal with heavily clothed humans (such as, suited astronauts) and to overcome the current limitations of wrongly identifying humans (either real or virtual) as univariate percentiles. We are looking at whole-body posture based anthropometric models as a means to identify humans of significantly different shapes and sizes to arrive at mathematically sound computer models for analytical purposes.
Spacecraft analysts in the spacecraft control center for the Cosmic Background Explorer (COBE) satellite are currently utilizing a fault-isolation expert system developed to assist in the isolation and correction of faults in the communications link. This system, the communication link expert assistance resource (CLEAR), monitors real time spacecraft and ground systems performance parameters in search of configuration discrepancies and communications link problems. If such a discrepancy or problem is isolated, CLEAR alerts the analyst and provides advice on how to resolve the problem swiftly and effectively. The CLEAR system is the first real time expert system to be used in the operational environment of a satellite control center at the NASA Goddard Space Flight Center. Clear has not only demonstrated the utility and potential of an expert system in the demanding environment of a satellite control center, but also has revealed many of the pitfalls and deficiencies of development of expert systems. One of the lessons learned from this and other initial expert system projects is that prototypes can often be developed quite rapidly, but operational expert systems require considerable effort. Development is generally a slow, tedious process that typically requires the special skills of trained programmers. Due to the success of CLEAR and several other systems in the control center domain, a large number of expert systems will certainly be developed to support control center operations during the early 1990's. To facilitate the development of these systems, a project was initiated to develop an integrated, domain-specific tool, the generic spacecraft analyst assistent (GenSAA), that alows the spacecraft analysts to rapidly create simple expert systems themselves. By providing a highly graphical point-and-select method of system development, GenSAA allows the analyst to utilize and/or modify previously developed rule bases and system components; thus, facilitating software reuse and reducing development time and effort.
Attention is called to several pitfalls that often beset investigators who make thermal emittance studies. The pitfalls mentioned include the following: (1) conflicting meanings of several frequently used terms as found in the literature, each meaning having authoritative sponsorship; (2) incomplete and hence potentially misleading descriptions of specimens on which reported data arc based; (3) reference to emissivity or remittance as a property of a surface rather than a volume property (influenced by the surface); (4) occasional omission of diffuse reflection from analyses of the optical properties of inhomogeneous bodies; (5) failure to observe the restrictions upon conditions that are required for validity of basic equations; (6)uncertainties as to the effective temperature, peculiar to specimens having low absorption indices; and (7) lack of suitable physical standards. Several suggestions are made for avoiding or minimizing the consequences of the pitfalls discussed.
Deep eutectic solvents (DES), on account of their low-cost, non-flammability and electrochemical stability, are attracting attention for their potential use in applications such as electrodeposition and energy storage. In these applications, knowledge of the transport and electrochemical kinetics properties of DES is critically important. To date, attempts to measure the kinetics parameters of the Cu 2+ + e ⇌ Cu 1+ reaction in ethaline DES have yielded a cathodic charge transfer coefficient (α) in the range of 0.2–0.3 suggesting an unexpected asymmetric polarization behavior. In the present work, we pursued a comprehensive study of the kinetics and transport properties of the aforementioned reaction. Using steady-state and transient polarization measurements on RDE and microelectrodes combined with diffusion-reaction modeling, we demonstrate that the Cu 2+ /Cu 1+ transition exhibits a charge transfer coefficient in the range of 0.49–0.54 and an exchange current density in the range 1.72–1.88 mA/cm 2 . Recommendations are provided for avoiding pitfalls in kinetics analysis of highly resistive DES electrolytes. These recommendations include the application of accurate $IR_Ω$ correction and the use of electrode configurations where the secondary current distribution is relatively uniform.
Copper (Cu) electrodes, as the most efficacious of CO 2 reduction reaction (CO 2 RR) electrocatalysts, serve as prototypes for determining and validating reaction mechanisms associated with electrochemical CO 2 reduction to hydrocarbons. As in situ electrochemical mechanism determination by experiments is still out of reach, such mechanistic analysis typically is conducted using density functional theory (DFT). The semilocal exchange-correlation (XC) approximations most often used to model such catalysis unfortunately engender a basic error: predicting the wrong adsorption site for CO (a key CO 2 RR intermediate) on the most ubiquitous facet of Cu, namely, Cu(111). This longstanding inconsistency casts lingering doubt on previous DFT predictions of the attendant CO 2 RR kinetics. Here, we apply embedded correlated wavefunction (ECW) theory, which corrects XC functional error, to study the CO 2 RR on Cu(111) via both surface hydride (*H) transfer and proton-coupled electron transfer (PCET). We predict that adsorbed CO (*CO) reduces almost equally to two intermediates, namely, hydroxymethylidyne (*COH) and formyl (*CHO) at –0.9 V vs the RHE. In contrast, semilocal DFT approximations predict a strong preference for *COH. With increasing applied potential, the dominance of *COH (formed via potential-independent surface *H transfer) diminishes, switching to the competitive formation of both *CHO and *COH (both formed via potential-dependent PCET). Furthermore, our results also demonstrate the importance of including explicitly modeled solvent molecules in predicting electron-transfer barriers and reveal the pitfalls of overreliance on simple surface *H transfer models of reduction reactions.
While technical training and advanced degree's assure proficiency at specific tasks within engineering disciplines, they fail to address the potential for communication breakdown and decision making errors familiar to multicultural environments where language barriers, intimidating personalities and interdisciplinary misconceptions exist. In an effort to minimize these pitfalls to effective panel review, NASA's lead safety engineers to the ISS Safety Review Panel (SRP), and Payload Safety Review Panel (PSRP) initiated training with their engineers, in conjunction with the panel chairs, and began a Panel Resource Management (PRM) program. The intent of this program focuses on the ability to reduce the barriers inhibiting effective participation from all panel attendees by bolstering participants confidence levels through increased communication skills, situational awareness, debriefing, and a better technical understanding of requirements and systems.
Observing System Simulation Experiments can be powerful tools for evaluating and exploring both the behavior of data assimilation systems and the potential impacts of future observing systems. With great power comes great responsibility - given a pure modeling framework, how can we be sure our results are meaningful? The challenges and pitfalls of OSSE calibration and validation will be addressed, as well as issues of incestuousness, selection of appropriate metrics, and experiment design. The use of idealized observational networks to investigate theoretical ideas in a fully complex modeling framework will also be discussed
Observing System Simulation Experiments can be powerful tools for evaluating and exploring both the behavior of data assimilation systems and the potential impacts of future observing systems. With great power comes great responsibility - given a pure modeling framework, how can we be sure our results are meaningful? The challenges and pitfalls of OSSE calibration and validation will be addressed, as well as issues of incestuousness, selection of appropriate metrics, and experiment design. The use of idealized observational networks to investigate theoretical ideas in a fully complex modeling framework will also be discussed.
Quantitatively accurate computational predictions of metal hydride thermodynamics are challenging but critical for alloy performance optimization across a multitude of technological domains, including hydrogen storage, compression, purification, and getters. Recent machine learning approaches have demonstrated great success in this area, but can potentially suffer from several shortcomings since they rely on imbalanced experimental training data and can have poor out-of-distribution (ood) test performance. Here, in this study, we circumvent such pitfalls by developing a computationally efficient, first principles-based workflow for direct prediction of metal hydride phase equilibrium, i.e., the pressure-composition-temperature (PCT) diagram. We then demonstrate its utility on predicting low stability hydrides derived from compositionally complex C14 Laves phase AB2 alloys. Specifically, we computationally predict and then experimentally validate an AB 2 alloy series (z < 0.6 for Ti 2−z Zr z CrMnFeNi) with ideal hydriding thermodynamics for a two-stage metal hydride-based compressor for pressurizing boil off from liquefied hydrogen. Importantly, this study lays the groundwork for accurate and efficient discovery/optimization of ood, low-stability hydrides for which purely data-driven approaches lack sufficient accuracy.
In this essay, a case study is presented on the electronic structure of several metal halide perovskites (MHP) using Kelvin probe (KP)-based surface photovoltage (SPV) measurements and ultraviolet photoemission spectroscopy (UPS) to demonstrate the advantages, but also the pitfalls, of using these techniques to characterize the surfaces of these materials. The first part addresses the loss of halide species from perovskite surfaces upon supragap illumination in vacuum. This has the potential to cause both a long-term alteration of the sample work function and a modification of the KP tip during SPV measurements. If undetected, this leads to a misinterpretation of the MHP surface potential. The second part illustrates the difficulties in determining the valence band maximum (VBM) of MHP surfaces with UPS and stresses the importance of taking into account the low density of states at the VBM edge. Given this circumstance, specific care must be taken to eliminate measurement artifacts in order to ascertain the presence or absence of low densities of electronic gap states above the VBM. This essay also highlights issues such as film degradation, nonequilibrium situations (e.g., SPV), and satellite emissions, which occur during photoemission spectroscopy.
Abstract New simulations at 12-km grid spacing with the Weather and Research Forecasting (WRF) Model nested in the MPI Earth System Model (ESM) are used to quantify possible changes in wind power generation potential as a result of global warming. Annual capacity factors (CF; measures of electrical power production) computed by applying a power curve to hourly wind speeds at wind turbine hub height from this simulation are also used to illustrate the pitfalls in seeking to infer changes in wind power generation directly from low-spatial-resolution and time-averaged ESM output. WRF-derived CF are evaluated using observed daily CF from operating wind farms. The spatial correlation coefficient between modeled and observed mean CF is 0.65, and the root-mean-square error is 5.4 percentage points. Output from the MPI-WRF Model chain also captures some of the seasonal variability and the probability distribution of daily CF at operating wind farms. Projections of mean annual CF (CF A ) indicate no change to 2050 in the southern Great Plains and Northeast. Interannual variability of CF A increases in the Midwest, and CF A declines by up to 2 percentage points in the northern Great Plains. The probability of wind droughts (extended periods with anomalously low production) and wind bonus periods (high production) remains unchanged over most of the eastern United States. The probability of wind bonus periods exhibits some evidence of higher values over the Midwest in the 2040s, whereas the converse is true over the northern Great Plains. Significance Statement Wind energy is playing an increasingly important role in low-carbon-emission electricity generation. It is a “weather dependent” renewable energy source, and thus changes in the global atmosphere may cause changes in regional wind power production (PP) potential. We use PP data from operating wind farms to demonstrate that regional simulations exhibit skill in capturing actual power production. Projections to the middle of this century indicate that over most of North America east of the Rocky Mountains annual expected PP is largely unchanged, as is the probability of extended periods of anomalously high or low production. Any small declines in annual PP are of much smaller magnitude than changes due to technological innovation over the last two decades.
Prior experiments reported by the authors have proven the hypothesis that achieving a dynamic temperature swing on the combustion chamber surface will lead to improved thermal and combustion efficiencies of the homogeneous charge compression ignition engine. A thin layer of yttria-stabilized zirconia, roughly 150 μm, was plasma sprayed on the piston top. It led to markedly advanced ignition and heat release in the gasoline homogeneous charge compression ignition engine, accompanied with reduced unburnt hydrocarbon and carbon monoxide emissions, improved combustion efficiency, and a higher thermal efficiency. A related computational study highlighted the critical role of coating thermal conductivity in achieving a desired dynamic response; hence, the second phase of experimental investigations focused on introducing structured porosity in the yttria-stabilized zirconia coating, as a means of reducing effective conductivity. Indeed, additional incremental improvements were observed, as well as limitations related to adverse effects of the surface roughness and the fuel interactions with the surface roughness and open pores. Erosion can also be a problem in a direct injection engine. Therefore, the third round of investigations focused on a material with a natively low conductivity (low-k), sprayed on the top of an Al piston in a relatively dense form, and in a way that yields a smooth surface. The objective was to capitalize on the low conductivity, while avoiding the pitfalls accompanying high-porosity formulations. The heat-storage capacity was limited by keeping the thickness relatively low. The results verify the paramount importance of thermal conductivity in the context of high “temperature swing” behavior and indicate a potential to improve the homogeneous charge compression ignition engine’s combustion efficiency roughly 1.5%, with the overall indicated efficiency improvement on the order of 5%, on a relative basis. In addition, the low-k oxide thermal barrier applied to the piston extended significantly the low-load homogeneous charge compression ignition operability limit.
In a nuclear or radiological event, an early diagnostic or prognostic tool is needed to distinguish unexposed from low- and highly exposed individuals with the latter requiring early and intensive medical care. Radiation-induced gene expression (GE) changes observed within hours and days after irradiation have shown potential to serve as biomarkers for either dose reconstruction (retrospective dosimetry) or the prediction of consecutively occurring acute or chronic health effects. The advantage of GE markers lies in their capability for early (1–3 days after irradiation), high-throughput, and point-of-care (POC) diagnosis required for the prediction of the acute radiation syndrome (ARS).
The Advancing Blade Concept (ABC) uses two rigid counterrotating rotors in a coaxial arrangement to provide advancing blades on both sides of the aircraft. This makes use of the high dynamic pressure on the advancing side of the rotors at high forward speed, virtually ignoring the low dynamic pressure on the retreating side, while still keeping the rotor system in roll trim. Theoretically such a rotor system will maintain its lift potential as speed increases. The XH-59A was designed to investigate this theory. A description is provided of the flight test program from May, 1980 to January, 1981. A summary is presented of the knowledge gained throughout the entire program, and current pitfalls are reviewed. It is concluded that the ABC has been verified, with the XH-59A envelope of blade lift coefficient as a function of advance ratio greatly exceeding that of conventional helicopter rotor systems.
The steps and procedures are described which are necessary to achieve a successful lightning-protection design for a state-of-the-art Full-Authority Digital Engine Control (FADEC) system. The engine and control systems used as examples are fictional, but the design and verification methods are real. Topics discussed include: applicable airworthiness regulation, selection of equipment transient design and control levels for the engine/airframe and intra-engine segments of the system, the use of cable shields, terminal-protection devices and filter circuits in hardware protection design, and software approaches to minimize upset potential. Shield terminations, grounding, and bonding are also discussed, as are the important elements of certification and test plans, and the role of tests and analyses. Also included are examples of multiple-stroke and multiple-burst testing. A review of design pitfalls and challenges, and status of applicable test standards such as RTCA DO-160, Section 22, are presented.
One of the main steps in gene-finding in prokaryotes is determining which open reading frames encode for a protein, and which occur by chance alone. There are many different methods to differentiate the two; the most prevalent approach is using shared homology with a database of known genes. This method presents many pitfalls, most notably the catch that you only find genes that you have seen before. The four most popular prokaryotic gene-prediction programs (GeneMark, Glimmer, Prodigal, Phanotate) all use a protein-coding training model to predict protein-coding genes, with the latter three allowing for the training model to be created ab initio from the input genome. Different methods are available for creating the training model, and to increase the accuracy of such tools, we present here GOODORFS, a method for identifying protein-coding genes within a set of all possible open reading frames (ORFS). Our workflow begins with taking the amino acid frequencies of each ORF, calculating an entropy density profile (EDP), using KMeans to cluster the EDPs, and then selecting the cluster with the lowest variation as the coding ORFs. To test the efficacy of our method, we ran GOODORFS on 14,179 annotated phage genomes, and compared our results to the initial training-set creation step of four other similar methods (Glimmer, MED2, PHANOTATE, Prodigal). We found that GOODORFS was the most accurate (0.94) and had the best F1-score (0.85), while Glimmer had the highest precision (0.92) and PHANOTATE had the highest recall (0.96).