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NASA NTRS2000

Multi-Disciplinary Design Optimization Using WAVE

The current preliminary design tools lack the product performance, quality and cost prediction fidelity required to design Six Sigma products. They are also frequently incompatible with the tools used in detailed design, leading to a great deal of rework and lost or discarded data in the transition from preliminary to detailed design. Thus, enhanced preliminary design tools are needed in order to produce adequate financial returns to the business. To achieve this goal, GEAE has focused on building the preliminary design system around the same geometric 3D solid model that will be used in detailed design. With this approach, the preliminary designer will no longer convert a flowpath sketch into an engine cross section but rather, automatically create 3D solid geometry for structural integrity, life, weight, cost, complexity, producibility, and maintainability assessments. Likewise, both the preliminary design and the detailed design can benefit from the use of the same preliminary part sizing routines. The design analysis tools will also be integrated with the 3D solid model to eliminate manual transfer of data between programs. GEAE has aggressively pursued the computerized control of engineering knowledge for many years. Through its study and validation of 3D CAD programs and processes, GEAE concluded that total system control was not feasible at that time. Prior CAD tools focused exclusively on detail part geometry and Knowledge Based Engineering systems concentrated on rules input and data output. A system was needed to bridge the gap between the two to capture the total system. With the introduction of WAVE Engineering from UGS, the possibilities of an engineering system control device began to formulate. GEAE decided to investigate the new WAVE functionality to accomplish this task. NASA joined GEAE in funding this validation project through Task Order No. 1. With the validation project complete, the second phase under Task Order No. 2 was established to develop an associative control structure (framework) in the UG WAVE environment enabling multi-disciplinary design of turbine propulsion systems. The capabilities of WAVE were evaluated to assess its use as a rapid optimization and productivity tool. This project also identified future WAVE product enhancements that will make the tool still more beneficial for product development.

Irwin, Keith↗

NASA NTRS2000

THRSTER: A Three-Stream Ejector Ramjet Analysis and Design Tool

An engineering tool for analyzing ejectors in rocket based combined cycle (RBCC) engines has been developed. A key technology for multi-cycle RBCC propulsion systems is the ejector which functions as the compression stage of the ejector ramjet cycle. The THRee STream Ejector Ramjet analysis tool was developed to analyze the complex aerothermodynamic and combustion processes that occur in this device. The formulated model consists of three quasi-one-dimensional streams, one each for the ejector primary flow, the secondary flow, and the mixed region. The model space marches through the mixer, combustor, and nozzle to evaluate the solution along the engine. In its present form, the model is intended for an analysis mode in which the diffusion rates of the primary and secondary into the mixed stream are stipulated. The model offers the ability to analyze the highly two-dimensional ejector flowfield while still benefits from the simplicity and speed of an engineering tool. To validate the developed code, wall static pressure measurements from the Penn-State and NASA-ART RBCC experiments were used to compare with the results generated by the code. The calculated solutions were generally found to have satisfactory agreement with the pressure measurements along the engines, although further modeling effort may be required when a strong shock train is formed at the rocket exhaust. The range of parameters in which the code would generate valid results are presented and discussed.

Chue, R. S.↗

NASA NTRS2000

THRSTER: A THRee-STream Ejector Ramjet Analysis and Design Tool

Chue, R. S.↗

NASA NTRS2002

26th JANNAF Airbreathing Propulsion Subcommittee Meeting

This volume, the first of four volumes, is a collection of 28 unclassified/unlimited-distribution papers which were presented at the Joint Army-Navy-NASA-Air Force (JANNAF) 26th Airbreathing Propulsion Subcommittee (APS) was held jointly with the 38th Combustion Subcommittee (CS), 20th Propulsion Systems Hazards Subcommittee (PSHS), and 2nd Modeling and Simulation Subcommittee. The meeting was held 8-12 April 2002 at the Bayside Inn at The Sandestin Golf & Beach Resort and Eglin Air Force Base, Destin, Florida. Topics covered include: scramjet and ramjet R&D program overviews; tactical propulsion; space access; NASA GTX status; PDE technology; actively cooled engine structures; modeling and simulation of complex hydrocarbon fuels and unsteady processes; and component modeling and simulation.

Fry, Ronald S.↗

NASA NTRS2007

Atmospheric Environments for Entry, Descent and Landing (EDL)

Scientific measurements of atmospheric properties have been made by a wide variety of planetary flyby missions, orbiters, and landers. Although landers can make in-situ observations of near-surface atmospheric conditions (and can collect atmospheric data during their entry phase), the vast majority of data on planetary atmospheres has been collected by remote sensing techniques from flyby and orbiter spacecraft (and to some extent by Earth-based remote sensing). Many of these remote sensing observations (made over a variety of spectral ranges), consist of vertical profiles of atmospheric temperature as a function of atmospheric pressure level. While these measurements are of great interest to atmospheric scientists and modelers of planetary atmospheres, the primary interest for engineers designing entry descent and landing (EDL) systems is information about atmospheric density as a function of geometric altitude. Fortunately, as described in in this paper, it is possible to use a combination of the gas-law relation and the hydrostatic balance relation to convert temperature-versus-pressure, scientific observations into density-versus-altitude data for use in engineering applications. The following section provides a brief introduction to atmospheric thermodynamics, as well as constituents, and winds for EDL. It also gives methodology for using atmospheric information to do "back-of-the-envelope" calculations of various EDL aeroheating parameters, including peak deceleration rate ("g-load"), peak convective heat rate. and total heat load on EDL spacecraft thermal protection systems. Brief information is also provided about atmospheric variations and perturbations for EDL guidance and control issues, and atmospheric issues for EDL parachute systems. Subsequent sections give details of the atmospheric environments for five destinations for possible EDL missions: Venus. Earth. Mars, Saturn, and Titan. Specific atmospheric information is provided for these destinations, and example results are presented for the "back-of-the-envelope" calculations mentioned above.

Justus, Carl G.↗

NASA NTRS2009

Exoplanet Community Report on Direct Infrared Imaging of Exoplanets

Direct infrared imaging and spectroscopy of exoplanets will allow for detailed characterization of the atmospheric constituents of more than 200 nearby Earth-like planets, more than is possible with any other method under consideration. A flagship mission based on larger passively cooled infrared telescopes and formation flying technologies would have the highest angular resolution of any concept under consideration. The 2008 Exoplanet Forum committee on Direct Infrared Imaging of Exoplanets recommends: (1) a vigorous technology program including component development, integrated testbeds, and end-to-end modeling in the areas of formation flying and mid-infrared nulling; (2) a probe-scale mission based on a passively cooled structurally connected interferometer to be started within the next two to five years, for exoplanetary system characterization that is not accessible from the ground, and which would provide transformative science and lay the engineering groundwork for the flagship mission with formation flying elements. Such a mission would enable a complete exozodiacal dust survey (<1 solar system zodi) in the habitable zone of all nearby stars. This information will allow for a more efficient strategy of spectral characterization of Earth-sized planets for the flagship missions, and also will allow for optimization of the search strategy of an astrometric mission if such a mission were delayed due to cost or technology reasons. (3) Both the flagship and probe missions should be pursued with international partners if possible. Fruitful collaboration with international partners on mission concepts and relevant technology should be continued. (4) Research and Analysis (R&A) should be supported for the development of preliminary science and mission designs. Ongoing efforts to characterize the the typical level of exozodiacal light around Sun-like stars with ground-based nulling technology should be continued.

Danchi, William C.↗

NASA NTRS2011

Implementation and Simulation Results using Autonomous Aerobraking Development Software

An Autonomous Aerobraking software system is currently under development with support from the NASA Engineering and Safety Center (NESC) that would move typically ground-based operations functions to onboard an aerobraking spacecraft, reducing mission risk and mission cost. The suite of software that will enable autonomous aerobraking is the Autonomous Aerobraking Development Software (AADS) and consists of an ephemeris model, onboard atmosphere estimator, temperature and loads prediction, and a maneuver calculation. The software calculates the maneuver time, magnitude and direction commands to maintain the spacecraft periapsis parameters within design structural load and/or thermal constraints. The AADS is currently tested in simulations at Mars, with plans to also evaluate feasibility and performance at Venus and Titan.

Maddock, Robert W.↗

NASA NTRS1994

Segmented Ion Engine Operation and Performance

The continuing trend toward smaller and smaller planetary spacecraft to enable the use of smaller, less expensive launch vehicles has motivated an examination of new approaches to reduce the size and mass of xenon ion propulsion systems for these new spacecraft. A system is proposed which is based on the use of a single 4x15-cm segmented ion thruster operated from a single internally redundant power processing unit. An engine input power throttling range of 380 to 4640 W is projected. The design and operation over a power range of 600 to 2400 W of a laboratory model segmented ion engine equipped with carbon-carbon grids is presented. There appear to be no problems associated with interactions with multiple ion sources operating from a single set of high voltage power supplies, neutralization of multiple ion sources from a single centrally located neutralizer, or operation of flat, thin carbon-carbon grids.

ion↗

NASA NTRS2008

Automatic Testcase Generation for Flight Software

The TacSat3 project is applying Integrated Systems Health Management (ISHM) technologies to an Air Force spacecraft for operational evaluation in space. The experiment will demonstrate the effectiveness and cost of ISHM and vehicle systems management (VSM) technologies through onboard operation for extended periods. We present two approaches to automatic testcase generation for ISHM: 1) A blackbox approach that views the system as a blackbox, and uses a grammar-based specification of the system's inputs to automatically generate *all* inputs that satisfy the specifications (up to prespecified limits); these inputs are then used to exercise the system. 2) A whitebox approach that performs analysis and testcase generation directly on a representation of the internal behaviour of the system under test. The enabling technologies for both these approaches are model checking and symbolic execution, as implemented in the Ames' Java PathFinder (JPF) tool suite. Model checking is an automated technique for software verification. Unlike simulation and testing which check only some of the system executions and therefore may miss errors, model checking exhaustively explores all possible executions. Symbolic execution evaluates programs with symbolic rather than concrete values and represents variable values as symbolic expressions. We are applying the blackbox approach to generating input scripts for the Spacecraft Command Language (SCL) from Interface and Control Systems. SCL is an embedded interpreter for controlling spacecraft systems. TacSat3 will be using SCL as the controller for its ISHM systems. We translated the SCL grammar into a program that outputs scripts conforming to the grammars. Running JPF on this program generates all legal input scripts up to a prespecified size. Script generation can also be targeted to specific parts of the grammar of interest to the developers. These scripts are then fed to the SCL Executive. ICS's in-house coverage tools will be run to measure code coverage. Because the scripts exercise all parts of the grammar, we expect them to provide high code coverage. This blackbox approach is suitable for systems for which we do not have access to the source code. We are applying whitebox test generation to the Spacecraft Health INference Engine (SHINE) that is part of the ISHM system. In TacSat3, SHINE will execute an on-board knowledge base for fault detection and diagnosis. SHINE converts its knowledge base into optimized C code which runs onboard TacSat3. SHINE can translate its rules into an intermediate representation (Java) suitable for analysis with JPF. JPF will analyze SHINE's Java output using symbolic execution, producing testcases that can provide either complete or directed coverage of the code. Automatically generated test suites can provide full code coverage and be quickly regenerated when code changes. Because our tools analyze executable code, they fully cover the delivered code, not just models of the code. This approach also provides a way to generate tests that exercise specific sections of code under specific preconditions. This capability gives us more focused testing of specific sections of code.

Bushnell, David Henry↗

DOE OSTI2017

Predicting Coculture Substrate Depletion (PCSD) v1

(based on Erbilgin et al., BMC Bioinformatics, 2017, 18:57). Mixed cultures of microbial species are increasingly used to carry out a specific task in lieu of engineering a single microbe to do the same task. However, knowing how different species' metabolisms will integrate to reach a desired outcome is a difficult problem that has been studied in great detail--but only using steady-state models. Mixed cultures used for biotechnology processes, as well as microbial communities that exist in nature and crop agriculture, are metabolically dynamic systems. Studying the temporal substrate utilization by individuals is individuals in mixed cultures is an important first step in developing approaches to better model these biochemical processes and microbial communities found in nature. The 2017-004 software is comprised of four custom iPython notebooks that were used for all computational tasks in the experimental work described in "Dynamic substrate preferences predict metabolic properties of a simple microbial consortium" (Erbilgin et al., BMC Bioinformatics, 2017). The results indicate that a significant portion of a model community's overall metabolism can be predicted based on the metabolism of the individuals. The results further suggest that, when the mixed culture's substrate depletion significantly deviates from such a prediction, this may highlight potential metabolic pathways affected by species-species microbial interactions, leading to hypotheses about how a particular microbial community's structure and function may be modulated to perform a particular biotechnological goal.

Bowen, Benjamin↗

DOE OSTI2021

Severity factor kinetic model as a strategic parameter of hydrothermal processing (steam explosion and liquid hot water) for biomass fractionation under biorefinery concept

Hydrothermal processes are an attractive clean technology and cost-effective engineering platform for bio-refineries based in the conversion of biomass to biofuels and high-value bioproducts under the basis of sustainability and circular bioeconomy. The deep and detailed knowledge of the structural changes by the severity of biomasses hydrothermal fractionation is scientifically and technological needed in order to improve processes effectiveness, reactors designs, and industrial application of the multi-scale target compounds obtained by stream explosion and liquid hot water systems. The concept of the severity factor [log 10 (R 0 )] established > 30 years ago, continue to be a useful index that can provide a simple description of the relationship between the operational conditions for biomass fractionation in second generation of biorefineries. Furthermore, this review develops a deep explanation of the hydrothermal severity factor based in lignocellulosic biomass fractionation with emphasis in research advances, pretreatment operations and the applications of severity factor kinetic model.

09 BIOMASS FUELS↗

NASA NTRS2016

Model-Based Engine Control Architecture with an Extended Kalman Filter

This paper discusses the design and implementation of an extended Kalman filter (EKF) for model-based engine control (MBEC). Previously proposed MBEC architectures feature an optimal tuner Kalman Filter (OTKF) to produce estimates of both unmeasured engine parameters and estimates for the health of the engine. The success of this approach relies on the accuracy of the linear model and the ability of the optimal tuner to update its tuner estimates based on only a few sensors. Advances in computer processing are making it possible to replace the piece-wise linear model, developed off-line, with an on-board nonlinear model running in real-time. This will reduce the estimation errors associated with the linearization process, and is typically referred to as an extended Kalman filter. The nonlinear extended Kalman filter approach is applied to the Commercial Modular Aero-Propulsion System Simulation 40,000 (C-MAPSS40k) and compared to the previously proposed MBEC architecture. The results show that the EKF reduces the estimation error, especially during transient operation.

engine control↗

DOE OSTI2021

Parsed synthesis of pyocyanin via co-culture enables context-dependent intercellular redox communication

Abstract Background Microbial co-cultures and consortia are of interest in cell-based molecular production and even as “smart” therapeutics in that one can take advantage of division of labor and specialization to expand both the range of available functions and mechanisms for control. The development of tools that enable coordination and modulation of consortia will be crucial for future application of multi-population cultures. In particular, these systems would benefit from an expanded toolset that enables orthogonal inter-strain communication. Results We created a co-culture for the synthesis of a redox-active phenazine signaling molecule, pyocyanin (PYO), by dividing its synthesis into the generation of its intermediate, phenazine carboxylic acid (PCA) from the first strain, followed by consumption of PCA and generation of PYO in a second strain. Interestingly, both PCA and PYO can be used to actuate gene expression in cells engineered with the soxRS oxidative stress regulon, although importantly this signaling activity was found to depend on growth media. That is, like other signaling motifs in bacterial systems, the signaling activity is context dependent. We then used this co-culture’s phenazine signals in a tri-culture to modulate gene expression and production of three model products: quorum sensing molecule autoinducer-1 and two fluorescent marker proteins, eGFP and DsRed. We also showed how these redox-based signals could be intermingled with other quorum-sensing (QS) signals which are more commonly used in synthetic biology, to control complex behaviors. To provide control over product synthesis in the tri-cultures, we also showed how a QS-induced growth control module could guide metabolic flux in one population and at the same time guide overall tri-culture function. Specifically, we showed that phenazine signal recognition, enabled through the oxidative stress response regulon soxRS, was dependent on media composition such that signal propagation within our parsed synthetic system could guide different desired outcomes based on the prevailing environment. In doing so, we expanded the range of signaling molecules available for coordination and the modes by which they can be utilized to influence overall function of a multi-population culture. Conclusions Our results show that redox-based signaling can be intermingled with other quorum sensing signaling in ways that enable user-defined control of microbial consortia yielding various outcomes defined by culture medium. Further, we demonstrated the utility of our previously designed growth control module in influencing signal propagation and metabolic activity is unimpeded by orthogonal redox-based signaling. By exploring novel multi-modal strategies for guiding communication and consortia outcome, the concepts introduced here may prove to be useful for coordination of multiple populations within complex microbial systems.

Chun, Kayla↗

DOE OSTI2021

Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants

An essential aspect of online monitoring, subtle anomaly detection increases the detection lead time for equipment failure and enables a nuclear power plant (NPP) to mitigate unexpected partial or full outages, resulting in significant cost saving to the plant. Once an anomaly is detected by plant staff, its cause and severity are investigated. Because the vast majority of anomalies require some level of investigation, including some that require time-consuming examination, before they are passed over to the engineering organization for further analysis, plants are often equipped with tools to assist the staff in performing anomaly detection. Those tools operate as a black box and are often based on statistical methods that establish sensor correlations using preconfigured mathematical models and flag correlation deviations as anomalies. Due to the number of anomalies detected at a given NPP on a daily basis, a significant number of flagged anomalies usually await examination for days or weeks. A primary cause of this backlog is that the methods used by the tools generate many false positives. Though this is usually attributed to oversensitive model settings due to very narrow normal operation bands, it can also be associated with the model development being inadequate for the process being monitored, or with missing model inputs that could have explained misclassified positives. The performance of anomaly detection tools impacts their plant acceptance and utilization, especially when the effort to address false positives generated by the tool depletes the value or cost saved by using that tool. Thus, means to advance anomaly detection performance have been investigated by the Department of Energy’s Light Water Reactor Sustainability program. Previous and ongoing efforts have targeted unsupervised machine-learning (ML) methods, which do not require the labeling of any data fed into the ML model. By contrast, in supervised anomaly detection methods, every data point is labeled as either a normal or abnormal process condition, and the model is trained to replicate the classification process. Supervised methods usually outperform unsupervised methods, due to the added value in differentiating normal from anomalous states of the monitored process. An NPP’s corrective action program requires it to track and document, via a dedicated report, the resolution of any issues that occur within the plant. Once created, each report is reviewed by a plant screening committee, and several classifications and decisions are made. Recently, a collaborating NPP developed an artificial intelligence and ML-based classifier to categorize a condition report (CR) into classes that can serve to label the data as normal or anomalous. Applying CRs as labels represents a semi-supervised use case. Semi-supervised ML assumes that labels exist for some data points (i.e., labeled anomalies, in this case) but not for the rest. In this effort, semi-supervised ML methods were used to fuse data from CRs with anomaly detection methods in order to test the hypothesis that partially labeled anomalies would improve the accuracy of the anomaly detection methods. Specifically, two methods were used. The first is the deep Semi-supervised Anomaly Detection (deep SAD) method, which can handle labels ranging from fully unsupervised to fully supervised cases. The second is a newly designed ML method developed specifically for this effort and referred to as the high-order feature (HOF)-based method. To evaluate these two methods in controlled environments, synthetic data generators were developed and used. The first datasets used a spring-mass-damper (SMD) system simulator commonly found in mechanical engineering references. This was used to create two use cases: a one- and a three-mass system. Anomalies were introduced by changing the spring and damper coefficients while the system was actuated by random forces. The second datasets used the commercial Dymola-Modelica software to build a simplified nuclear reactor model. Anomalies were added in the form of corrupted sensor readings and/or control commands. The deep SAD method was tested using the SMD system, while the HOF method was tested using both datasets. Application of the deep SAD semi-supervised ML method demonstrated that labels can generate increased confidence in detecting true anomalies. This helped increase the number of true positives and decrease the number of false negatives—something that would aid in addressing the backlog of possible anomalies. Application of the HOF method demonstrated that labels can aid in down selecting from a candidate set of features to a more optimal subset in order to better differentiate between normal and anomalous conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

A cell-free system for production of 2,3-butanediol is robust to growth-toxic compounds

The need for sustainable, low-cost production of bioenergy and commodity chemicals is increasing. Unfortunately, the engineering potential of whole-cell catalysts to address this need can be hampered by cellular toxicity. When such bottlenecks limit the commercial feasibility of whole-cell fermentation, cell-free, or in vitro, based approaches may offer an alternative. Here, we assess the impact of three classes of growth toxic compounds on crude extract-based, cell-free chemical conversions. As a model system, we test a metabolic pathway for conversion of glucose to 2,3-butanediol (2,3-BDO) in lysates of Escherichia coli . First, we characterized 2,3-BDO production with different classes of antibiotics and found, as expected, that the system is uninhibited by compounds that prevent cell growth by means of cell wall replication and DNA, RNA, and protein synthesis. Second, we considered the impact of polar solvent addition (e.g., methanol, n-butanol). We observed that volumetric productivities (g/L/h) were slowed with increasing hydrophobicity of added alcohols. Finally, we investigated the effects of using pretreated biomass hydrolysate as a feed stock, observing a 25% reduction in 2,3-BDO production as a result of coumaroyl and feruloyl amides. Overall, we find the cell-free system to be robust to working concentrations of antibiotics and other compounds that are toxic to cell growth, but do not denature or inhibit relevant enzymes.

09 BIOMASS FUELS↗

DOE OSTI2026

T-FSM: A Scalable Distributed Task-Based System for Frequent Subgraph Pattern Mining from a Big Graph

Finding frequent subgraph patterns in a big graph is an important problem with many applications such as classifying chemical compounds and building indexes to speed up graph queries. Since this problem is NP-hard, some recent parallel and distributed systems have been developed to accelerate the mining. However, they often have a huge memory cost, very long running time, suboptimal load balancing, poor scale-out capability, and possibly inaccurate results. In this article, we propose an efficient system called T-FSM for parallel mining of frequent subgraph patterns in a big graph. T-FSM supports a new anti-monotonic frequentness measure called Fraction-Score, which is more accurate than the widely used MNI measure. The execution engine of T-FSM supports both intra-machine parallelism and inter-machine parallelism. For intra-machine parallelism, T-FSM adopts a novel task-based execution model to ensure high multithreading concurrency, bounded memory consumption, and effective load balancing. For inter-machine parallelism, T-FSM ensures good scale-out performance with a lightweight pattern rebalancing approach that reduces workload skewness of pattern evaluations among machines. To avoid recomputing the contexts for migrated patterns, we design a novel context cache table to support concurrent and asynchronous requesting and caching of remote context data, which can timely evict and garbage collect used pattern contexts that are no longer needed to keep memory consumption bounded. Extensive experiments show that T-FSM is orders of magnitude faster than existing state-of-the-art parallel systems (more than 10×, 51×, 131×, 55× speedup over ScaleMine, DistGraph, Pangolin and Peregrine, respectively) and distributed systems (more than 42× and 88× over ScaleMine and DistGraph, respectively) for frequent subgraph pattern mining, and it scales out satisfactorily to 512 CPU cores on the Polaris supercomputer at Argonne National Laboratory.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2017

Assessing Tactical Scheduler Options for Time-Based Surface Metering

NASA is committed to demonstrating a concept of integrated arrival, departure, and surface operations by 2020 under the Airspace Technology Demonstration 2 (ATD2) sub-project. This will be accomplished starting with a demonstration of flight specific time-based departure metering at Charlotte Douglass International Airport (CLT). ATD2 tactical metering capability is based on NASAs Spot And Runway Departure Advisor (SARDA) which has been tested successfully in human-in-the-loop simulations of CLT. SARDA makes use of surface surveillance data and surface modeling to estimate the earliest takeoff time for each flight active on the airport surface or ready for pushback from the gate. The system then schedules each flight to its assigned runway in order of earliest takeoff time and assigns a target pushback time, displayed to ramp controllers as an advisory gate hold time. The objective of this method of departure metering is to move as much delay as possible to the gate to minimize surface congestion and engine on-time, while keeping sufficient pressure on the runway to maintain throughput. This flight specific approached enables greater flight efficiency and predictability, facilitating trajectory-based operations and surface-airspace integration, which ATD2 aims to achieve.Throughout ATD2 project formulation and system development, researchers have continuously engaged with stakeholders and future users, uncovering key system requirements for tactical metering that SARDA did not address. The SARDA scheduler is updated every 10 seconds using real-time surface surveillance data to ensure the most up-to-date information is used to predict runway usage. However, rapid updates also open the potential for fluctuating advisories, which Ramp controllers at a busy airport like CLT find unacceptable. Therefore, ATD2 tactical metering requires that all advisories freeze once flights are ready so that Ramp controllers may communicate a single hold time when responding to pilot ready calls.

Zelinski, Shannon↗

DOE OSTI2017

Realization of a Hole-Doped Mott Insulator on a Triangular Silicon Lattice

The physics of doped Mott insulators is at the heart of some of the most exotic physical phenomena in materials research including insulator-metal transitions, colossal magnetoresistance, and high-temperature superconductivity in layered perovskite compounds. Advances in this field would greatly benefit from the availability of new material systems with a similar richness of physical phenomena but with fewer chemical and structural complications in comparison to oxides. In this paper, using scanning tunneling microscopy and spectroscopy, we show that such a system can be realized on a silicon platform. The adsorption of one-third monolayer of Sn atoms on a Si(111) surface produces a triangular surface lattice with half filled dangling bond orbitals. Modulation hole doping of these dangling bonds unveils clear hallmarks of Mott physics, such as spectral weight transfer and the formation of quasiparticle states at the Fermi level, well-defined Fermi contour segments, and a sharp singularity in the density of states. These observations are remarkably similar to those made in complex oxide materials, including high-temperature superconductors, but highly extraordinary within the realm of conventional $sp$-bonded semiconductor materials. Finally, it suggests that exotic quantum matter phases can be realized and engineered on silicon-based materials platforms.

36 MATERIALS SCIENCE↗