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At least 379 records · Page 21

A constraint-based framework for exploring the impact of multireaction dependencies on metabolic functions

Abstract Metabolism operates under physico-chemical constraints that result in multireaction dependencies. Understanding how multireaction dependencies affect metabolic phenotypes remains challenging, hindering their biotechnological applications. Here, we propose the concept of a forcedly balanced complex that allows to efficiently determine the effects of specific multireaction dependencies on metabolic network functions in constrained-based models. Using this concept, we found that the fraction of multireaction dependencies induced by forcedly balanced complexes in genome-scale metabolic networks followed power law with exponential cut-off. We identified forcedly balanced complexes that are lethal in cancer but have little effect on growth in healthy tissue models. In addition, these forcedly balanced complexes are largely specific to models of particular cancer types. Therefore, multireaction dependencies resulting from forced balancing of complexes represent an innovative means to control cancers that, we argue, can be implemented via transporter engineering. The presented constraint-based approaches pave the way for using multireaction dependencies in metabolic engineering for diverse biotechnological applications.

Küken, Anika↗

Sensitivity analysis of the effect of wind and wake characteristics on wind turbine loads in a small wind farm

Abstract. Wind turbines are designed using a set of simulations to determine the fatigue and ultimate loads, which are typically focused solely on unwaked wind turbine operation. These structural loads can be significantly influenced by the wind inflow conditions. Turbines experience altered inflow conditions when placed in the wake of upstream turbines, which can additionally influence the fatigue and ultimate loads. It is important to understand the impact of uncertainty on the resulting loads of both unwaked and waked turbines. The goal of this work is to assess which wind-inflow-related and wake-related parameters have the greatest influence on fatigue and ultimate loads during normal operation for turbines in a three-turbine wind farm. Twenty-eight wind inflow and wake parameters are screened using an elementary effects sensitivity analysis approach to identify the parameters that lead to the largest variation in the fatigue and ultimate loads of each turbine. This study uses the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine, simulated with OpenFAST and synthetically generated inflow based on the International Electrotechnical Commission (IEC) Kaimal turbulence spectrum with the IEC exponential coherence model using the NREL tool TurbSim. The focus is on sensitivity to individual parameters, though interactions between parameters are considered, and how sensitivity differs between waked and unwaked turbines. The results of this work show that for both waked and unwaked turbines, ambient turbulence in the primary wind direction and shear are the most sensitive parameters for turbine fatigue and ultimate loads. Secondary parameters of importance for all turbines are identified as yaw misalignment, streamwise integral length, and the exponent and streamwise components of the IEC coherence model. The tertiary parameters of importance differ between waked and unwaked turbines. Tertiary effects account for up to 9.0 % of the significant events for waked turbine ultimate loads and include veer, non-streamwise components of the IEC coherence model, Reynolds stresses, wind direction, air density, and several wake calibration parameters. For fatigue loads, tertiary effects account for up to 5.4 % of the significant events and include vertical turbulence standard deviation, lateral and vertical wind integral lengths, non-streamwise components of the IEC coherence model, Reynolds stresses, wind direction, and all wake calibration parameters. This information shows the increased importance of non-streamwise wind components and wake parameters in the fatigue and ultimate load sensitivity of downstream turbines.

17 WIND ENERGY↗

Quantum simulation of real-space dynamics

Quantum simulation is a prominent application of quantum computers. While there is extensive previous work on simulating finite-dimensional systems, less is known about quantum algorithms for real-space dynamics. We conduct a systematic study of such algorithms. In particular, we show that the dynamics of a d-dimensional Schrödinger equation with η particles can be simulated with gate complexity O ~ (ηdFpoly(log(g'/ϵ))), where ϵ is the discretization error, g' controls the higher-order derivatives of the wave function, and F measures the time-integrated strength of the potential. Compared to the best previous results, this exponentially improves the dependence on ϵ and g' from poly(g'/ϵ) to poly(log(g'/ϵ)) and polynomially improves the dependence on T and d, while maintaining best known performance with respect to η. For the case of Coulomb interactions, we give an algorithm using η 3 (d + η)Tpoly(log(ηdTg'/(Δϵ)))/Δ one- and two-qubit gates, and another using η 3 (4d) d/2 Tpoly(log(ηdTg'/(Δϵ)))/Δ one- and two-qubit gates and QRAM operations, where T is the evolution time and the parameter Δ regulates the unbounded Coulomb interaction. We give applications to several computational problems, including faster real-space simulation of quantum chemistry, rigorous analysis of discretization error for simulation of a uniform electron gas, and a quadratic improvement to a quantum algorithm for escaping saddle points in nonconvex optimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Combined X-Ray and Gamma Ray Study of the Seyfert Galaxies NGC 7469 and NGC 3227

The Seyfert galaxy NGC 7469 has been observed with both the OSSE instrument on the Compton Observatory at hard x-ray energies, and with both the PCA and HEXTE detectors on the Rossi XTE satellite. The OSSE spectral data were combined with ASCA and Ginga spectra. The combined spectrum is largely consistent with a Compton reflection model, with a weakly constrained exponential cutoff above 50 keV. Significant flux variability was observed in the x-ray data, and the XTE data are being used to better under- stand the combined x-ra and gamma ray spectrum. and to measure spectral and flux variability with greater accuracy. At the present time, background subtraction uncertainty in the XTE data is still being refined, which is limiting the study of time variability. Work has recently been slowed bN, my participation in the launch and operations of the Chandra Observatory.

Cameron, Robert↗

An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.

Novikau, I [Lawrence Livermore National Laboratory↗

Damage Propagation Modeling for Aircraft Engine Prognostics

This paper describes how damage propagation can be modeled within the modules of aircraft gas turbine engines. To that end, response surfaces of all sensors are generated via a thermo-dynamical simulation model for the engine as a function of variations of flow and efficiency of the modules of interest. An exponential rate of change for flow and efficiency loss was imposed for each data set, starting at a randomly chosen initial deterioration set point. The rate of change of the flow and efficiency denotes an otherwise unspecified fault with increasingly worsening effect. The rates of change of the faults were constrained to an upper threshold but were otherwise chosen randomly. Damage propagation was allowed to continue until a failure criterion was reached. A health index was defined as the minimum of several superimposed operational margins at any given time instant and the failure criterion is reached when health index reaches zero. Output of the model was the time series (cycles) of sensed measurements typically available from aircraft gas turbine engines. The data generated were used as challenge data for the Prognostics and Health Management (PHM) data competition at PHM 08.

Saxena, Abhinav↗

Compression of transmission bandwidth requirements for a certain class of band-limited functions.

A study of source-encoding techniques that afford a reduction of data-transmission rates is made with particular emphasis on the compression of transmission bandwidth requirements of band-limited functions. The feasibility of bandwidth compression through analog signal rooting is investigated. It is found that the N-th roots of elements of a certain class of entire functions of exponential type possess contour integrals resembling Fourier transforms, the Cauchy principal values of which are compactly supported on an interval one N-th the size of that of the original function. Exploring this theoretical result, it is found that synthetic roots can be generated, which closely approximate the N-th roots of a certain class of band-limited signals and possess spectra that are essentially confined to a bandwidth one N-th that of the signal subjected to the rooting operation. A source-encoding algorithm based on this principle is developed that allows the compression of data-transmission requirements for a certain class of band-limited signals.

Smith, I. R.↗

Analysis of Convective Weather Impact on Pre-Departure Routing of Flights from Fort Worth Center to New York Center

In response to severe weather conditions, Traffic Managers specify flow constraints and reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options and associated airspace capacities would assist Traffic Managers in making more efficient decisions in response to convective weather. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. This paper describes the initial steps and methodology used towards this goal. The focus of this work is flights departing from Fort Worth Center destined for New York Center. Dominant routing structures used in the absence of convective weather are identified. A method to extract relevant features from the large volume of weather data available to quantify the impact of convective weather on this routing structure over a given time range is presented. Finally, a method of estimating flow rate capacity along commonly used routes during convective weather events is described. Results show that the flow rates drop exponentially as a function of the values of the proposed feature and that convective weather on the final third of the route was found to have a greater impact on the flow rate restriction than other portions of the route.

traffic flow management↗

Revealing the loss mechanisms of a 3D superconducting microwave cavity for use in a dark matter search

Superconducting microwave cavities have found applications in many areas including quantum computing, particle accelerators, and dark matter searches. Their extremely high quality factors translate to very narrow bandwidth, which makes them key components of sensitive detectors. In this study, we aim to understand the loss mechanisms of an aluminium cavity, with a fundamental mode frequency of about 2.5123 GHz, and how they change as the cavity material transitions from the superconducting to normal state. We found that at temperatures not much lower than the transition temperature $T_c$, losses are dominated by quasiparticle excitations and are well described by the Bardeen–Cooper–Schrieffer theory. The exponential decrease of the quasiparticle density below $T_c$ results in a 1000-fold increase of the quality factor, as well as a shift of the resonance frequency due to the change of the kinetic inductance of the superconductor. At very low temperatures, losses due to two-level systems begin to dominate giving a peak in the quality factor of about 2.76 x 10 7 at 130 mK. Understanding the loss mechanisms is invaluable, as the working temperature of the cavity may vary during operation regardless of its application.

Physics - Physics of elementary particles and fiel↗

Suomi-NPP VIIRS Solar Diffuser Stability Monitor Performance

When illuminated by the Sun, the onboard solar diffuser (SD) panel provides a known spectral radiance source to calibrate the reflective solar bands of the Visible Infrared Imaging Radiometer Suite on the Suomi-NPP satellite. The SD bidirectional reflectance distribution function (BRDF) degrades over time due to solar exposure, and this degradation is measured using the SD stability monitor (SDSM). The SDSM acts as a ratioing radiometer, comparing solar irradiance measurements off the SD panel to those from a direct Sun view. We discuss the design and operations of the SDSM, the SDSM data analysis, including improvements incorporated since launch, and present the results through 1000 days after launch. After 1000 days, the band-dependent H-factors, a quantity describing the relative degradation of the BRDF of the SD panel since launch, range from 0.716 at 412 nanometers to 0.989 at 926 nanometers. The random uncertainty of these H-factors is about 0.1 percent, which is confirmed by the similar standard deviation values computed from the residuals of quadratic exponential fits to the H-factor time trends. The SDSM detector gains have temperature sensitivity of up to about 0.36 percent per kelvin, but this does not affect the derived H-factors. An initial error in the solar vector caused a seasonal bias to the H-factors of up to 0.5 percent. The total exposure of the SD panel to UV light after 1000 orbits is equivalent to about 100 hours of direct sunlight illumination perpendicular to the SD panel surface.

Fulbright, Jon↗

The Cooling Loop A Anomaly of 2013: A Case Study in Human-Systems Resilience

Throughout the history of human spaceflight, NASA has employed an operational paradigm of 24/7 dependence on experts in Mission Control Center (MCC). In addition to nominal flight control and mission operations, these 85+ experts per shift manage anomaly detection, diagnosis, and response, and support the crew in real-time in performing maintenance and repair, procedure execution, and other complex mission operations. Future long-duration exploration missions (LDEMs) beyond low-Earth orbit (LEO) will not operate successfully using this same Human-Systems Integration Architecture (HSIA) where crew rely on ground controllers, have ready access to resupply, and have a fallback plan of evacuation. As distance from Earth increases and the communication delay grows, crews will need to respond independently and adequately to time-critical vehicle malfunctions. It will not always be sufficient or even possible to ‘safe the system’ and then wait upon ground intervention. A new and radically different HSIA is needed to accommodate the paradigm shift of deep-space travel. Historical International Space Station (ISS) data show that for a 30-day mission, the likelihood of a high-consequence vehicle anomaly of uncertain origin that requires rapid response is greater than 10%. The likelihood of such an event is 50% by the fourth month of the mission, and it grows exponentially with time. Our team has conducted in-depth investigations into these events and their corresponding anomaly resolution activities. Using MCC and Mission Evaluation Room (MER) anomaly resolution artifacts (including meeting summaries, caution and warning data, and ISS daily summaries), we created timelines detailing ground actions and in-orbit events for two significant anomalies. We then mapped these timelines onto Mars transit conditions, introducing a ground-crew communications time delay and shifting immediate response, time-critical task execution, and vehicle commanding to the crew. In detailing successful anomaly resolution in transit to Mars, the timelines highlight where effective resolution requires drastically evolved onboard capabilities. Though this research has yielded a rich data set based on ground response in past missions, there is still insufficient knowledge to assess the potential impact of inflight anomalies on a small autonomous crew on future LDEMs beyond LEO. To begin building an evidence base that will inform future HSIA standards and requirements, we are developing an approach to systematically capture crew anomaly response and procedure execution during early Artemis missions. Being the first human spaceflight beyond LEO since Apollo, early Artemis missions provide a rare and unique opportunity to serve as a testbed for Mars missions. Our work aims to capitalize on planned data collection to derive crew operational responses to anomalous events in real-time. Our team is also researching the level of simulation fidelity required for empirically validating proposed HSIA standards and evaluating HSIA implementations for LDEMs beyond LEO. This work will produce a trade space study of HSIA simulation objectives and fidelity requirements. Ultimately, these research efforts will assist in developing the standards and technologies needed to build a next-generation HSIA for LDEMs beyond LEO.

human-systems integration architecture↗

Giovanni in the Cloud: Earth Science Data Exploration in Amazon Web Services

Giovanni is an exploration tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), providing 22 analysis and visualization services for over 1600 Earth Science data variables. Owing to its popularity, Giovanni has experienced a consistent growth in overall demand, with periodic usage spikes attributed to trainings by education organizations, extensive data analysis in response to natural disasters, preparations for science meetings, etc. Furthermore, the new generation of spaceborne sensors and high resolution models have resulted in an exponential growth in data volume with data distributed across the traditional boundaries of data centers. Seamless exploration of data (without users having to worry about data center boundaries) has been a key recommendation of the GES DISC User Working Group. These factors have required new strategies for delivering acceptable performance. The cloud-based Giovanni, built on Amazon Web Services (AWS), evaluates (1) AWS native solutions to provide a scalable, serverless architecture; (2) open standards for data storage in the Cloud; (3) a cost model for operations; and (4) end-user performance. Our preliminary findings indicate that the use of serverless architecture has a potential to significantly reduce development and operational cost of Giovanni. The combination of using AWS managed services, storage of data in open standards, and schema-on-read data access strategy simplifies data access and analytics, in addition to making data more accessible to the end users of Giovanni through popular programming languages.

Giovanni↗

Real‐time XFEL data analysis at SLAC and NERSC: A trial run of nascent exascale experimental data analysis

X‐ray scattering experiments using free electron lasers (XFELs) are a powerful tool to determine the molecular structure and function of unknown samples (such as COVID‐19 viral proteins). XFEL experiments are a challenge to computing in two ways: (i) due to the high cost of running XFELs, a fast turnaround time from data acquisition to data analysis is essential to make informed decisions on experimental protocols; (ii) data‐collection rates are growing exponentially, requiring new scalable algorithms. Here we report our experiences analyzing data from two experiments at the Linac Coherent Light Source (LCLS) during September 2020. Raw data were analyzed on NERSC's Cori XC40 system, using the Superfacility paradigm: our workflow automatically moves raw data between LCLS and NERSC, where it is analyzed using the software package CCTBX. We achieved real time data analysis with a turnaround time from data acquisition to full molecular reconstruction in as little as 10 min—sufficient time for the experiment's operators to make informed decisions. By hosting the data analysis on Cori, and by automating LCLS‐NERSC interoperability, we achieved a data analysis rate which matches the data acquisition rate. Completing data analysis within 10 min is a first for XFEL experiments and an important milestone if we are to keep up with data‐collection trends.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Using a Grid-Forming Inverter to Stabilize a Low-Inertia Power System - Maui Hawaiian Island

As power systems around the world integrate greater amounts of wind and solar photovoltaic power, periods of very high instantaneous power shares of inverters, the primary interfacing technology for these generation sources, are complicating system stability and control. The contemporary, primary mode of inverter operation, grid-following, which explicitly assumes the presence of a local, stable voltage waveform, yields operational inadequacy at high instantaneous power shares potentially leading to instability due to the low-inertia conditions, as well as the correlated reduced voltage forming capacity on the respective system. Parallel connected grid-forming inverters, which directly regulate the local voltage, are a solution that is expected to bolster system stability and mitigate the shortcomings of the grid-following technology. In this paper, grid-following and two types of grid-forming inverter control, the traditional linear droop and the recently introduced nonlinear exponential droop (Droop-e), are simulated on a low-inertia, H = 0.48s, high inverter-based resource scenario, 97%, with a validated electromagentic transient domain model of the Hawaiian island of Maui power system. The benefit of a single grid-forming device over its grid-following counterpart is significant, both in terms frequency deviation and voltage stability. Further, the superiority of the Droop-e and the associated secondary power sharing control over both grid-following and linear droop grid-forming technologies is displayed, with improved nadir and rate of change of frequency over the linear droop control.

droop control↗

Real-Time XFEL Data Analysis at SLAC and NERSC: a Trial Run of Nascent Exascale Experimental Data Analysis

X-ray scattering experiments using Free Electron Lasers (XFELs) are a powerful tool to determine the molecular structure and function of unknown samples (such as COVID-19 viral proteins). XFEL experiments are a challenge to computing in two ways: i) due to the high cost of running XFELs, a fast turnaround time from data acquisition to data analysis is essential to make informed decisions on experimental protocols; ii) data collection rates are growing exponentially, requiring new scalable algorithms. Here we report our experiences analyzing data from two experiments at the Linac Coherent Light Source (LCLS) during September 2020. Raw data were analyzed on NERSC's Cori XC40 system, using the Superfacility paradigm: our workflow automatically moves raw data between LCLS and NERSC, where it is analyzed using the software package CCTBX. We achieved real time data analysis with a turnaround time from data acquisition to full molecular reconstruction in as little as 10 min -- sufficient time for the experiment's operators to make informed decisions. By hosting the data analysis on Cori, and by automating LCLS-NERSC interoperability, we achieved a data analysis rate which matches the data acquisition rate. Furthermore, completing data analysis with 10 mins is a first for XFEL experiments and an important milestone if we are to keep up with data collection trends.

Blaschke, Johannes P.↗

Extraction of Qualitative Features from Sensor Data Using Windowed Fourier Transform

In this paper, we use Matlab to model the health monitoring of a system through the information gathered from sensors. This implies assessment of the condition of the system components. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of an element, a qualitative change, or a change due to a problem with another element in the network. For example, if one sensor indicates that the temperature in the tank has experienced a step change then a pressure sensor associated with the process in the tank should also experience a step change. The step up and step down as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system is allowed to run for a period equal to three time constant of the main process before changes occur. Then each point of the signal is selected with a trailing data collected previously. Two trailing lengths of data are selected, one equal to two time constants of the main process and the other equal to two time constants of the sensor disturbance. Next, the DC is removed from each set of data and then the data are passed through a window followed by calculation of spectra for each set. In order to extract features the signal power, peak, and spectrum are plotted vs time. The results indicate distinct shapes corresponding to each process. The study is also carried out for a number of Gaussian distributed noisy cases.

Amini, Abolfazl M.↗

Subleading power resummation of rapidity logarithms: the energy-energy correlator in $ \mathcal{N} $ = 4 SYM

We derive and solve renormalization group equations that allow for the resummation of subleading power rapidity logarithms. Our equations involve operator mixing into a new class of operators, which we term the “rapidity identity operators”, that will generically appear at subleading power in problems involving both rapidity and virtuality scales. To illustrate our formalism, we analytically solve these equations to resum the power suppressed logarithms appearing in the back-to-back (double light cone) limit of the Energy-Energy Correlator (EEC) in \( \mathcal{N} \) = 4 super-Yang-Mills. These logarithms can also be extracted to \( \mathcal{O}\left({\alpha}_s^3\right) \) from a recent perturbative calculation, and we find perfect agreement to this order. Instead of the standard Sudakov exponential, our resummed result for the subleading power logarithms is expressed in terms of Dawson’s integral, with an argument related to the cusp anomalous dimension. We call this functional form “Dawson’s Sudakov”. Our formalism is widely applicable for the resummation of subleading power rapidity logarithms in other more phenomenologically relevant observables, such as the EEC in QCD, the p T spectrum for color singlet boson production at hadron colliders, and the resummation of power suppressed logarithms in the Regge limit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Splines under tension in integral transfer problems

Splines under tension are used to develop an interpolatory representation of integral radiation operators. A quantitative measure of the stability of this representation is derived and approximated in terms of local grid lengths and the tension parameter. Cubic splines (zero tension parameter) are shown to be approximately stable when the ratio of successive grid lengths lies within a specific range. Scaling procedures for determining the tension constant from the structure of the grids and the characteristics of the problem are discussed, and the utility of these procedures is illustrated by application to the formation of resonance lines in two-dimensional media with exponential height variation of opacity.

Jones, H. P.↗