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At least 559 records · Page 31

Discrete Fourier Transform Analysis in a Complex Vector Space

Alternative computational strategies for the Discrete Fourier Transform (DFT) have been developed using analysis of geometric manifolds. This approach provides a general framework for performing DFT calculations, and suggests a more efficient implementation of the DFT for applications using iterative transform methods, particularly phase retrieval. The DFT can thus be implemented using fewer operations when compared to the usual DFT counterpart. The software decreases the run time of the DFT in certain applications such as phase retrieval that iteratively call the DFT function. The algorithm exploits a special computational approach based on analysis of the DFT as a transformation in a complex vector space. As such, this approach has the potential to realize a DFT computation that approaches N operations versus Nlog(N) operations for the equivalent Fast Fourier Transform (FFT) calculation.

Dean, Bruce H.↗

Preliminary Jitter Stability Results for the Large UV/Optical/Infrared (LUVOIR) Surveyor Concept Using a Non-Contact Vibration Isolation and Precision Pointing System

The need for high payload dynamic stability and ultra-stable mechanical systems is an overarching technology need for large space telescopes such as the Large Ultraviolet / Optical / Infrared (LUVOIR) Surveyor concept. The LUVOIR concept includes a 15-meter-diameter segmented-aperture telescope with a suite of serviceable instruments operating over a range of wavelengths between 100nm to 2.5 um. Wavefront error (WFE) stability of less than 10 picometers RMS of uncorrected system WFE per wavefront control step represents a drastic performance improvement over current space-based telescopes being fielded. Through the utilization of an isolation architecture that involves no mechanical contact between the telescope and the host spacecraft structure, a system design is realized that maximizes the telescope dynamic stability performance without driving stringent technology requirements on spacecraft structure, sensors or actuators. Through analysis of the LUVOIR finite element model and linear optical model, the wavefront error and Line-Of-Sight (LOS) jitter performance is discussed in this paper when using the Vibration Isolation and Precision Pointing System (VIPPS) being developed cooperatively with Lockheed Martin in addition to a multi-loop control architecture. The multi-loop control architecture consists of the spacecraft Attitude Control System (ACS), VIPPS, and a Fast Steering Mirror on the instrument. While the baseline attitude control device for LUVOIR is a set of Control Moment Gyroscopes (CMGs), Reaction Wheel Assembly (RWA) disturbance contribution to wavefront error stability and LOS stability are presented to give preliminary results in this paper. CMG disturbance will be explored in further work to be completed.

Sacks, Lia W.↗

Additively Printed Flexible Temperature Sensor for Wearable Applications

The flexible sensor has the capability to be mounted on any curved surfaces of applications and be used for portable devices. Additively printed sensors have received attention owing to their compact design and ability of application to non-planar surfaces. Wearable applications require capability of integration into a variety of surfaces with ability to flex, fold, twist and stretch under the stresses of daily motion. There is scarcity of data on the interaction of the process parameters with the realized performance. In addition, there is need for data focused on sensor accuracy, repeatability, and reliability. In this study, experimental analysis on function of the fabricated sensing board is conducted. The temperature sensors are made by direct write printing method with nScrypt printer. A calibration of the sensors has been conducted to confirm that resistance is well related to actual temperature and find TCR (temperature coefficient to resistance). The evolution of resistance has been correlated with the environmental temperature. The sensor hysteresis has been quantified using upswing and downswing of the environmental temperature. In addition, the effect of humidity on the temperature sensor accuracy and performance has been quantified. The effect of a polymide coat on the sensor to prevent humidity effects has also been quantified.

Pradeep Lall↗

Evaluation and Interpretation of Properties for Saltstone Cores Extracted from an SDU - 17344

Extraction and subsequent analysis of emplaced saltstone samples from a Savannah River Site (SRS) Saltstone Disposal Unit (SDU) were performed in order to realize the following key objectives: (1) to support the use of historical and future laboratory-derived sample data to predict the behavior of field-emplaced samples, and (2) to substantiate the saltstone properties currently assumed in Saltstone Disposal Facility (SDF) transport modeling, i.e., Performance Assessment (PA) and Special Analyses (SA) models. Multiple cores were extracted via a wet core drilling process in April-May 2015 approximately 20 months after the saltstone of interest was processed in the Saltstone Production Facility (SPF) and subsequently emplaced in SDU Cell 2A (SDU2A). The retrieved samples were stored in an inert N{sub 2} environment prior to, and during, the property testing that took place between October 2015 and March 2016. Sample analyses comprised evaluation of physical properties (density, porosity, and moisture content), saturated hydraulic conductivity (K{sub sat}), and determination of distribution coefficients and solubilities for key radionuclides. In general the SDU2A samples indicated comparative properties to laboratory-prepared samples and additionally verified many of the inputs currently assumed in the SDF PA. The principal exception was related to the leaching characteristics of I-129, which demonstrated a lower than anticipated affinity for retention within the saltstone matrix. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Paradigm Shift continued: An Application of Structured Decision Making for Sustainable Waste Management - 16486

Structured decision making presents an opportunity for DOE and others engaged in solving complex environmental and waste management problems to find solutions that are stakeholder engaged and cost effective. This approach represents a paradigm shift that was introduced in a series of papers and a panel session at the WM2015 Symposium. The advantages of structured decision making over less formal approaches to decision making include technical defensibility, traceability and transparency. Structured decision making also overcomes the limitations of misapplication of conservatism in modeling, addresses stakeholder concerns and competing objectives directly, and provides a formal method through which internal and external stakeholders are encouraged to collectively and carefully consider all relevant attributes of solving complex problems. The first requirement of this paradigm shift is a realization and recognition that the problems faced are inherently decision problems, and that there is a formal theory of decision analysis that can, and should, be used to support finding the best solutions. Structured decision making is, very simply, formalized common sense. The formalities include: framing the problem; identification of objectives and measures for valuing those objectives; costs or values associated with those objectives; management options or alternatives for taking action that are tied directly to the objectives; and, science-based models to evaluate the options. Decision analysis is used to evaluate objectives and choose management options by balancing probability and consequence. The science-based models are built probabilistically based on expectation and uncertainty, and costs and value judgments are used to fulfill addressing stakeholder concerns. Consequently, this approach avoids misplaced conservatism in science-based modeling and properly places values in the objectives component of a decision model. This approach honestly addresses uncertainty and value judgments and balances these competing components to find the most effective decision. A software framework program called Guided Interactive Statistical Decision Tools (GiSdT - pronounced 'gist') is used to support an application of this paradigm shift towards structured decision making. In this application objectives and management options for a waste disposal problem at the Los Alamos National Laboratory are identified, and features, events and processes are described and defined to form the basis of a conceptual site model. This establishes the decision model structure. Objectives are addressed through the three pillars of sustainability - economic, environmental, and social - and also address regulatory concerns or constraints. Management options include removal of waste to another location and engineering designs for leaving waste in place. Using structured decision making, the relationship between objectives, management options, and the conceptual site model is made clear, and leads to a comprehensive, defensible, transparent and traceable approach to effective decision making. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Intelligent Hardware-Enabled Sensor and Software Safety and Health Management for Autonomous UAS

Unmanned Aerial Systems (UAS) can only be deployed if they can effectively complete their mission and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. We propose to design a real-time, onboard system health management (SHM) capability to continuously monitor essential system components such as sensors, software, and hardware systems for detection and diagnosis of failures and violations of safety or performance rules during the ight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the- y temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power hardware realization using Field Programmable Gate Arrays (FPGAs) in order to avoid overburdening limited computing resources or costly re-certi cation of ight software due to instrumentation. No currently available SHM capabilities (or combinations of currently existing SHM capabilities) come anywhere close to satisfying these three criteria yet NASA will require such intelligent, hardwareenabled sensor and software safety and health management for introducing autonomous UAS into the National Airspace System (NAS). We propose a novel approach of creating modular building blocks for combining responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. Our proposed research program includes both developing this novel approach and demonstrating its capabilities using the NASA Swift UAS as a demonstration platform.

Robotics↗

Accelerating Science Impact through Big Data Workflow Management and Supercomputing

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. ATLAS, one of the largest collaborations ever assembled in the the history of science, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. To manage the workflow for all data processing on hundreds of data centers the PanDA (Production and Distributed Analysis)Workload Management System is used. An ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF), is realizing within BigPanDA and megaPanDA projects. These projects are now exploring how PanDA might be used for managing computing jobs that run on supercomputers including OLCF’s Titan and NRC-KI HPC2. The main idea is to reuse, as much as possible, existing components of the PanDA system that are already deployed on the LHC Grid for analysis of physics data. The next generation of PanDA will allow many data-intensive sciences employing a variety of computing platforms to benefit from ATLAS experience and proven tools in highly scalable processing.

97 MATHEMATICS AND COMPUTING↗

North American extreme precipitation events and related large-scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends

This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defned based on the characteristic spatial variations of a meteorological feld or on the remote circulation response to a known forcing, LSMPs are defned relative to the occurrence of a specifc phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary infuence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to defnitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many diferent defnitions of “extreme” are in use, making it difcult to directly compare diferent studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identifed and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.

Barlow, Mathew↗

Design and Analysis of Turbines for Space Applications

In order to mitigate the risk of rocket propulsion development, efficient, accurate, detailed fluid dynamics analysis of the turbomachinery is necessary. This analysis is used for component development, design parametrics, performance prediction, and environment definition. To support this requirement, a task was developed at NASAh4arshall Space Flight Center (MSFC) to improve turbine aerodynamic performance through the application of advanced design and analysis tools. There are four major objectives of this task: 1) to develop, enhance, and integrate advanced turbine aerodynamic design and analysis tools; 2) to develop the methodology for application of the analytical techniques; 3) to demonstrate the benefits of the advanced turbine design procedure through its application to a relevant turbine design point; and 4) to verify the optimized design and analysis with testing. The turbine chosen on which to demonstrate the procedure was a supersonic design suitable for a reusable launch vehicle (RLV). The hot gas path and blading were redesigned to obtain an increased efficiency. The redesign of the turbine was conducted with a consideration of system requirements, realizing that a highly efficient turbine that, for example, significantly increases engine weight, is of limited benefit. Both preliminary and detailed designs were considered. To generate an improved design, one-dimensional (1D) design and analysis tools, computational fluid dynamics (CFD), response surface methodology (RSM), and neural nets (NN) were used.

Griffin, Lisa W.↗

DOE/DOT Crude Oil Characterization Research Study, Task 2 Test Report on Evaluating Crude Oil Sampling and Analysis Methods, Revision 1 - Winter Sampling

The Crude Oil Characterization Research Study is designed to evaluate whether crude oils currently transported in North America, including those produced from “tight” formations, exhibit physical or chemical properties that are distinct from conventional crudes, and how these properties associate with combustion hazards that may be realized during transportation and handling. The current report presents results from Task 2, investigating which commercially available methods can accurately and reproducibly collect and analyze crude oils for vapor pressure and composition, including dissolved gases. This issue, Revision 1 – Winter Sampling, incorporates additional seasonal data and compositional analysis results that have become available since publication of a prior report, SAND2017-12482, released in December 2017. Both reports compare performance of commercially available methods to that of a well-established mobile laboratory system that currently serves as the baseline instrument system for the U.S. Strategic Petroleum Reserve Crude Oil Vapor Pressure Program. The experimental matrix evaluates the performance of selected methods for (i) capturing, transporting, and delivering hydrocarbon fluid samples from the field to the analysis laboratory, coupled with (ii) analyzing for properties related to composition and volatility of the oil, including vapor pressure, gas-oil ratio, and dissolved gases and light hydrocarbons. Several combinations of sample capture and analysis were observed to perform well in both summer and winter sampling environments, though conditions apply that need to be considered carefully for given applications. Methods that perform well from Task 2 will then be utilized in subsequent Task 3 (combustion studies) and Task 4 (compositional analyses of multiple crude types), to be addressed in subsequent reports.

02 PETROLEUM↗

Interpretation of AMS-02 electrons and positrons data

We perform a combined analysis of the recent AMS-02 data on electrons, positrons, electrons plus positrons and positron fraction, in a self-consistent framework where we realize a theoretical modeling of all the astrophysical components that can contribute to the observed fluxes in the whole energy range. The primary electron contribution is modeled through the sum of an average flux from distant sources and the fluxes from the local supernova remnants in the Green catalog. The secondary electron and positron fluxes originate from interactions on the interstellar medium of primary cosmic rays, for which we derive a novel determination by using AMS-02 proton and helium data. Primary positrons and electrons from pulsar wind nebulae in the ATNF catalog are included and studied in terms of their most significant (while loosely known) properties and under different assumptions (average contribution from the whole catalog, single dominant pulsar, a few dominant pulsars). We obtain a remarkable agreement between our various modeling and the AMS-02 data for all types of analysis, demonstrating that the whole AMS-02 leptonic data admit a self-consistent interpretation in terms of astrophysical contributions.

79 ASTRONOMY AND ASTROPHYSICS↗

Realization of the axial next-nearest-neighbor Ising model in U 3 Al 2 Ge 3

In this paper, we report small-angle neutron scattering (SANS) measurements and theoretical modeling of U 3 Al 2 Ge 3 . Analysis of the SANS data reveals a phase transition to sinusoidally modulated magnetic order at T N = 63 K to be second order and a first-order phase transition to ferromagnetic order at T c = 48 K. Within the sinusoidally modulated magnetic phase (T c < T < T N ), we uncover a dramatic change, by a factor of 3, in the ordering wave vector as a function of temperature. Finally, these observations all indicate that U 3 Al 2 Ge 3 is a close realization of the three-dimensional axial next-nearest-neighbor Ising model, a prototypical framework for describing commensurate to incommensurate phase transitions in frustrated magnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Excitonic Condensate in Flat Valence and Conduction Bands of Opposite Chirality

Excitonic Bose-Einstein condensation (EBEC) has drawn increasing attention recently with the emergence of 2D materials. A general criterion for EBEC, as expected in an excitonic insulator (EI) state, is to have negative exciton formation energies in a semiconductor. Here, using exact diagonalization of a multiexciton Hamiltonian modeled in a diatomic kagome lattice, we demonstrate that the negative exciton formation energies are only a prerequisite but insufficient condition for realizing an EI. By a comparative study between the cases of both conduction and valence flat bands (FBs) versus that of a parabolic conduction band, we further show that the presence and increased FB contribution to exciton formation provide an attractive avenue to stabilize the excitonic condensate, as confirmed by calculations and analyses of multiexciton energies, wave functions, and reduced density matrices. In conclusion, our results warrant a similar many-exciton analysis for other known and/or new candidates of EIs and demonstrate the FBs of opposite parity as a unique platform for studying exciton physics, paving the way to material realization of spinor BEC and spin superfluidity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Evaluation of Hydrogen Production Feasibility for a Light Water Reactor in the Midwest

Increased electricity production from renewable energy resources coupled with low natural gas prices has caused existing light-water reactor (LWRs) to experience ever diminishing returns from the electricity market. Via partnership among Idaho National Laboratory (INL), The National Renewable Energy Laboratory (NREL), Argonne National Laboratory (ANL), Exelon, and Fuel Cell Energy a techno-economic analysis on the viability of retrofitting existing pressurized water reactors (PWRs) to produce hydrogen (H2) via high temperature steam electrolysis (HTSE) has been conducted. Such integration would allow nuclear facilities to expand into additional markets that may be more profitable in the long-term. To accommodate such an integration, a detailed analysis of HTSE process operation, requirements, and flexibility was conducted. Technical analysis includes proposed nuclear system control scheme modifications to allow dynamic operation of the HTSE via both thermal and electrical connection to the nuclear plant. High fidelity Modelica simulations showcase the viability of such control schemes. However, due to limited knowledge of solid oxide fuel cell (SOFC) stack degradation due to thermal gradients; thermal cycling of the HTSE was not included. Therefore, the control schemes proposed are only utilized to re-distribute steam at startup and only the portion of electricity utilized in the electrolyzers is cycled. From the detailed analysis of the nuclear integration and the HTSE process design, a comprehensive cost estimation was conducted in the APEA and H2A models to elucidate capital and operational costs associated with the production, compression, and distribution of hydrogen from a nuclear facility. Alongside this costing analysis, market analyses were conducted by NREL and ANL on the electric and hydrogen markets respectively in the PJM interconnect. Utilizing the electricity data market projections in the PJM interconnect from NREL and hydrogen demand/pricing projections from ANL a five variable sweep over component capacities, discount rates, and hydrogen pricing was completed using the stochastic framework RAVEN (Risk Analysis Virtual ENVironment) through its resource dispatch plugin HERON (Heuristic Energy Resource Optimization Network). Each combination of variables was evaluated stochastically four times over a seventeen year timespan from 2026-2042 (inclusive) to determine the most economically advantageous solution. Following the five variable sweep an optimization was conducted about the best sweep point to determine optimal component sizing and setpoints. Results suggest positive gain is achievable at all projected hydrogen market pricing levels and at all discount rates. However, exact component sizing and net returns vary based on these values and if incorrect sizing is selected; major net losses can occur. The optimal result occurred with set points as follows: high hydrogen prices, the largest possible HTSE unit in the sweep set at 7.47 kg/sec [645.4 tpd], a contractual hydrogen market agreement 7.29 kg/sec [629.8 tpd], and a hydrogen storage size 115,188 kg. The analysis suggested that with a discount rate of 8%, a ΔNPV = 1.2 billion over the seventeen year span can be achieved. The results illuminate that by operating in multiple markets the nuclear facility is capable of avoiding sale of electricity during times of low electricity market pricing, while maintaining the ability to capitalize on the high electricity market pricing. It should be noted that the analysis conducted in this report is a differential cash flow analysis and as such does not present profit levels. Instead it highlights the net benefit between building and competing in the hydrogen market utilizing nuclear facilities and conducting business as usual in the electricity markets. Additionally, results presented in this report exhibit conservatism due to four key assumptions: Given the limited knowledge on SOFC stack degradation due to thermal gradients the high temperature steam electrolysis plant is not allowed to thermally cycle. This limitation decreases electricity generation capacity in the nuclear plant, reducing capacity payments and the maximum output to the electrical grid. This analysis considers building a separate hydrogen pipeline for use in the nuclear facility. Research is currently being conducted to determine if existing natural gas pipelines can accommodate direct hydrogen injection. If hydrogen can be integrated into existing natural gas pipelines then a capital savings of ~$19,000,000 per kg/sec [1 kg/sec = 86.4 tpd] of installed HTSE capacity could be realized. Fast transients in the electric grid are typically served by flywheels and electric batteries. With electrolysis only operation the nuclear plant can flex its electricity just as quickly. However, for this analysis, the ancillary services market has been neglected. Should the nuclear plant have the ability to operate in the ancillary services market during periods when it is producing hydrogen, an additional substantial income stream that would increase overall system profitability could be considered. Subsidies for non-emitting generation technologies are not introduced in the cash flow analysis, but instead are completed assuming zero subsidies. Profitability is based solely on electricity pricing. Electric pricing is assumed to never go negative. Instead, it is assumed overall system curtailment by the Independent System Operator (ISO) will occur in such a manner that pricing remains at or above zero. This assumption inflates the “business as usual” scenario, thus decreasing the ΔNPV calculated. If negative pricing scenarios continue to occur as they do today, one would expect a further increase in ΔNPV. Overall, results advocate that, through market diversification, nuclear power plants have the potential to substantially increase current profit margins, increase market penetration, and ultimately solidify their place as a mainstay in energy production.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Characterizing the Sample Selection for Supernova Cosmology

Type Ia supernovae (SNe Ia) are used as distance indicators to infer the cosmological parameters that specify the expansion history of the universe. Parameter inference depends on the criteria by which the analysis SN sample is selected. Only for the simplest selection criteria and population models can the likelihood be calculated analytically, otherwise it needs to be determined numerically, a process that inherently has error. Numerical errors in the likelihood lead to errors in parameter inference. This article presents toy examples where the distance modulus is inferred given a set of SNe at a single redshift. Parameter estimators and their uncertainties are calculated using Monte Carlo techniques. The relationship between the number of Monte Carlo realizations and numerical errors is presented. The procedure can be applied to more realistic models and used to determine the computational and data management requirements of the transient analysis pipeline.

79 ASTRONOMY AND ASTROPHYSICS↗

Advanced Automation for Ion Trap Mass Spectrometry-New Opportunities for Real-Time Autonomous Analysis

The utility of MS/MS for both target compound analysis and the structure elucidation of unknowns has been described in a number of references. A broader acceptance of this technique has not yet been realized as it requires large, complex, and costly instrumentation which has not been competitive with more conventional techniques. Recent advancements in ion trap mass spectrometry promise to change this situation. Although the ion trap's small size, sensitivity, and ability to perform multiple stages of mass spectrometry have made it eminently suitable for on-line, real-time monitoring applications, advance automation techniques are required to make these capabilities more accessible to non-experts. Towards this end we have developed custom software for the design and implementation of MS/MS experiments. This software allows the user to take full advantage of the ion trap's versatility with respect to ionization techniques, scan proxies, and ion accumulation/ejection methods. Additionally, expert system software has been developed for autonomous target compound analysis. This software has been linked to ion trap control software and a commercial data system to bring all of the steps in the analysis cycle under control of the expert system. These software development efforts and their utilization for a number of trace analysis applications will be described.

Palmer, Peter T.↗

Analysis of the Spectral Stability of the Generalized Runge–Kutta Methods Applied to Initial-Boundary-Value Problems for Equations of the Parabolic Type. II. Implicit Methods

We consider specific realizations of different implicit generalized Runge–Kutta methods as applied to the numerical integration with respect to time of initial-boundary-value problems for the second-order parabolic equations and investigate their spectral stability. It is shown that all implicit generalized Runge–Kutta methods are unconditionally spectrally stable but some of them have the conditional property of monotonicity of the numerical solution with respect to time. The functions of spectral stability of the implicit generalized Runge–Kutta methods are rational. We compare the analytic solution of the nonstationary one-dimensional problem of heat conduction with the numerical solutions of this problem obtained by different implicit generalized Runge–Kutta methods. It is shown that, in this case, the application of the one-stage Radau methods with subsequent discretization of the problem with respect to the space variable leads to the classical forward finite difference scheme (Laasonen scheme), whereas the use of the one-stage Gauss–Legendre method leads to a six-point symmetric scheme (Crank–Nicolson scheme). It is shown that diagonally implicit generalized Nørsett and Burrage methods are realized in almost the same way as the one-stage Radau and Gauss–Legendre methods but their accuracy in the time step is 10–1000 times higher. On the basis of comparison of the numerical and analytic solutions, we conclude that, in order to get practically suitable numerical solutions without any restrictions on the time step, it is reasonable to use one- and three-stage generalized Radau methods or two- and four-stage Lobatto IIIC methods. All other explicit and implicit generalized Runge–Kutta methods require certain restrictions imposed on the time step.

42 ENGINEERING↗

Establishment of CRISPR/Cas9-Mediated Knock-in System for Porcine Cells with High Efficiency

Since the birth of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9, the new genome engineering technology has become a hot topic in the scientific community. However, for swine, the system of pig cells’ homology directed repair (HDR) is generally unstable and costly. Here, we aim to make knock-in of porcine cells more realizable. The Rosa26 locus was chosen for gene editing. Through the optimization of strategy, an efficient sgRNA was selected by TIDE analysis. Correspondingly, a vector system was constructed for gene insertion in pRosa26 locus by homologous recombination. A large percentage of cells whose gene is edited easily result in apoptosis. To improve the positive rate, culturing systems have been optimized. Sequence alignment and nuclear transfer confirmed that we got two knock-in cell lines and transgene primary porcine fetal fibroblasts (PFFs) successfully. Results showed that the gene editing platform we used can obtain genetically modified pig cells stably and efficiently. This system can contribute to pig gene research and production of transgenic pigs.

60 APPLIED LIFE SCIENCES↗