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Sampling, quantization, and channel errors in differential pulse-code modulation (DPCM) systems are considered and compared to results obtained with standard pulse-code modulation (PCM) systems. DPCM and PCM are compared for three different reconstruction filters. The optimum prediction coefficient is shown to depend on the channel noise.-
A pulse code modulated communication system is disclosed for transmitting two subcarrier modulated carriers from a single transmitter comprising two channels for phase modulating the two carriers independently. The modulating subcarriers are independently modulated by data and/or pseudonoise (PN) codes as desired. The modulated carriers are switched alternately to the single transmitter in synchronism with operation of a PN code generator when PN code modulation is present, as for ranging.
The performance of NASA Telecommand System was analyzed. A random coding approach was taken to determine the optimum code rate to use in forward error correcting (FEC) system with a fixed signal energy to noise power density ration, but no bandwidth constraint. Capacity and cutoff rates of concatened coding systems were determined. A lower bound on the minium distance growth rate between unmerged codewords was obtained for time invarient convolutional codes.
The airborne integrated flight test data system (AIFTDS) is described. This system integrates an airborne digital computer with a high-bit-rate pulse code modulation system. Its design was influenced by in-house technical experience with similar modules and by the multiproject environment in which it was expected to operate. The present work describes events leading to the development of the system, reviews factors that influenced the objectives for the system and the resulting design, and describes the elements themselves. Block diagrams supplement the text.
Synchronization times reduced to reduce loss of data. Scheme for decoding received doubly encoded binary-data signal provides for joint synchronization of two decoders. Applies to concatenated error-correcting channel coding communication system in which, at transmitter, data first encoded by interleaved Reed-Solomon code (block code), then by convolutional code.
A method and system for performing pattern analysis with a neural network coarse-coding a pattern to be analyzed so as to form a plurality of sub-patterns collectively defined by data. Each of the sub-patterns comprises sets of pattern data. The neural network includes a plurality fields, each field being associated with one of the sub-patterns so as to receive the sub-pattern data therefrom. Training and testing by the neural network then proceeds in the usual way, with one modification: the transfer function thresholds the value obtained from summing the weighted products of each field over all sub-patterns associated with each pattern being analyzed by the system.
A single-chip implementation of a Reed-Solomon encoder with interleaving capability is described. The code used was adapted by the CCSDS (Consulative Committee on Space Data Systems). It forms the outer code of the NASA standard concatenated coding system which includes a convolutional inner code of rate 1/2 and constraint length 7. The architecture, leading to this single VLSI chip design, makes use of a bit-serial finite field multiplication algorithm due to E.R. Berlekamp.
Computational models for the flight experiment demonstration system (FEDS) code 580 were developed. The FEDS is a modification of the automated orbit determination system which was developed during 1981 and 1982. The purpose of FEDS is to demonstrate, in a simulated spacecraft environment, the feasibility of using microprocessors to perform onboard orbit determination with limited ground support.
The method of pseudocompressibility is being tested for its accuracy in solving the incompressible Navier-Stokes equations. An implicit, finite-difference computer code is used to solve the equations in a three-dimensional, curvilinear coordinate system. The code employs artificial compressibility for solving the pressure field, coupled with an implicit, approximate-factorization scheme. This coupling is known as the pseudocompressibility method. The pseudocompressibility method introduces pressure waves of finite speed into the fluid medium that would otherwise have an infinite sound speed. The waves die out as the solution converges, and the steady state solution approaches a divergence-free condition. However, these waves limit the time-accuracy of the computations. The effects of these waves are analyzed and criteria are set for choosing the pseudocompressibility parameters that govern the pressure wave speed. Test cases are presented that verify these criteria. The code is tested by computing laminar flow over a two-dimensional, backward-facing step and over a two-dimensional, impulsively started circular cylinder.
The method of pseudocompressibility is tested for its accuracy in solving the incompressible Navier-Stokes equations. An implicit, finite difference computer code is used to solve the equations in a three-dimensional, curvilinear coordinate system. The code employs artificial compressibiity for solving the pressure field, coupled with an implicit, approximate factorization scheme. This coupling is known as the pseudocompressibility method and introduces pressure waves of finite speed into the fluid medium that would otherwise have an infinite sound speed. The waves die out as the solution converges, and the steady state solution approaches a divergence-free condition. These waves, however, limit the time accuracy of the computations. The effects of these waves are analysed and criteria are set for choosing the pseudocompressibility parameter that governs the pressure wave speed; test cases are presented that verify these criteria. The code is tested by computing laminar flow over a two-dimensional, backward-facing step and over a two-dimensional, impulsively started circular cylinder.
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The CTT code is a compilation of the python code that was prototyped in the interest of making a method for fine alignment of Flash X-ray Systems at the lab. It contains python code for interacting with LTT and running optimization loops using LTT simulations or ray tracing with RaySpace. It Includes classes for creating phantom objects and modular geometry objects in the simulations. It allows one to generate a random phantom that has been optimized to stay with a certain cubic volume and maximize the minimum distance between any two ball phantom centers in all projections. It was primarily made to work on ball phantoms which were simulated as Teflon spheres. It allows the alignment from some nominal position to some displaced position to simulate recovery of a real geometry from the nominal geometry of the system. Fine alignment can be done with the projections in LTT while a rough alignment is faster using rayspace. If rayspace works well for the use case it should be preferred since it is considerably faster and less resource intensive in general. Some Notes about using this code is that one will have to edit the imports for the files to get to the correct LTT path, LTT GUI path and to the CTT path when importing. This was made by using anaconda with python 3 on windows 10. The LTT code was stored in a anaconda environment which seemed to help the python find the LTT although it shouldn’t be necessary if you append the path in your code using sys.path.append(r'add the path you want here’). The sys.path.append method is a quick way to give your python code access to a given folder when running it (such as LTT or CTT). Note that since the code was originally made with paths for a specific machine that a new user will have to edit those paths to make it work in all the files that use the old paths. This is somewhat tedious but will be required to run the code on a new machine. The methodology used to run and make these notebooks starts with opening a command prompt as administrator in windows 10. After this one would activate the anaconda environment in the appropriate directory using “conda activate myenv” in the command prompt. After this open a jupyter-notebook using the keyword “jupyter-notebook". After that a notebook should open in a browser. Note that some libraries used may not come with anaconda so those may have to be installed. There shouldn’t be much though since the main things used are scipy, numpy, matplotlib, and LTT. LTTQuicksetup also requires some paths that will be specific to the computer so that should be changed as well.
In recent years, there has been renewed interest in molten salt reactors (MSRs) for their potential advantages compared to reactors that rely on solid fuel. In response to such interest, many methods and codes have been developed to capture the unique features of MSRs. Among them, SPECTRA and SAM are two system analysis codes that have been enhanced to include MSR-specific modeling capabilities, including delayed neutron precursor drift and modified point kinetics equations.This paper discusses the efforts taken to verify and validate these features. A standard MSR system test problem was developed to verify and demonstrate the capability of SPECTRA and SAM on the MSR transient simulation. Sixteen transients were simulated. Further, the results obtained from SPECTRA and SAM show good agreement. The Molten Salt Reactor Experiment transient experiments were reviewed and selected to validate the SPECTRA and SAM codes. The experiments included pump startup and coastdown tests at zero power, reactivity insertion tests at different power levels, frequency tests, and a natural convection test. The simulation results from SPECTRA and SAM show good agreement with the experimental data.
All vision systems, both human and machine, transform the spatial image into a coded representation. Particular codes may be optimized for efficiency or to extract useful image features. Researchers explored image codes based on primary visual cortex in man and other primates. Understanding these codes will advance the art in image coding, autonomous vision, and computational human factors. In cortex, imagery is coded by features that vary in size, orientation, and position. Researchers have devised a mathematical model of this transformation, called the Hexagonal oriented Orthogonal quadrature Pyramid (HOP). In a pyramid code, features are segregated by size into layers, with fewer features in the layers devoted to large features. Pyramid schemes provide scale invariance, and are useful for coarse-to-fine searching and for progressive transmission of images. The HOP Pyramid is novel in three respects: (1) it uses a hexagonal pixel lattice, (2) it uses oriented features, and (3) it accurately models most of the prominent aspects of primary visual cortex. The transform uses seven basic features (kernels), which may be regarded as three oriented edges, three oriented bars, and one non-oriented blob. Application of these kernels to non-overlapping seven-pixel neighborhoods yields six oriented, high-pass pyramid layers, and one low-pass (blob) layer.
Abstract Bacillus subtilis is a model gram-positive bacterium, commonly used to explore questions across bacterial cell biology and for industrial uses. To enable greater understanding and control of proteins in B. subtilis , here we report broad and efficient genetic code expansion in B. subtilis by incorporating 20 distinct non-standard amino acids within proteins using 3 different families of genetic code expansion systems and two choices of codons. We use these systems to achieve click-labelling, photo-crosslinking, and translational titration. These tools allow us to demonstrate differences between E. coli and B. subtilis stop codon suppression, validate a predicted protein-protein binding interface, and begin to interrogate properties underlying bacterial cytokinesis by precisely modulating cell division dynamics in vivo. We expect that the establishment of this simple and easily accessible chemical biology system in B. subtilis will help uncover an abundance of biological insights and aid genetic code expansion in other organisms.
The US nuclear industry is looking to improve on the operating economics of the current fleet of light-water reactors (LWRs). One way of achieving this is by operating fuel to higher burnup. In pressurized water reactors (PWRs), relaxing the current burnup limit will allow for cycle length extensions and power uprates; in boiling water reactors (BWRs) it may allow for improved fuel utilization and reduced feed assemblies, as well as more efficient power uprates and increased capacity factors that will support the Administration’s Executive Order to facilitate 5 GW of power uprates at existing nuclear facilities. However, one of the key limitations to operating fuel to higher burnup is the risk of fuel fragmentation, relocation, and dispersal (FFRD). Recognizing the high interest in extending burnup limits, the US Nuclear Regulatory Commission (NRC) has issued Draft Regulatory Guide DG-1434, which defines an approach that would be acceptable to the NRC for addressing FFRD risk. The approach defined will require better understanding of the phenomena leading to FFRD as well as best-estimate simulation methods to understand FFRD risk in high-burnup cores. The Nuclear Energy Advanced Modeling and Simulation program is supporting the FFRD industry challenge problem through development of state-of-the-art, high-fidelity modeling and simulation LWR analysis capabilities; namely, the BISON fuel performance code and the VERA core simulator software. These tools, along with the US NRC TRACE system analysis code, have been utilized for analysis of FFRD risk in both PWR and BWR cores in recent years. The work documented in this report addresses the lack of high-fidelity research for BWRs and builds on a previous activity where the framework has been applied to Cycles 16 through 18 of Limerick Unit 1, a BWR/4, with introduction of 8 high-burnup lead use assemblies (HBLUAs) that were representative of the 8 HBLUAs loaded into Limerick Unit 2 in 2021. VERA was used in this previous activity to model rod-by-rod depletion in these cycles, and its solution was used to initialize a TRACE simulation of a large-break loss-of-coolant accident (LBLOCA) at the end of Cycle 18. In the work documented in this report, the TRACE model was improved by refining the core mesh and utilizing a new feature that allows for capturing the full 3D VERA power distribution in the model. This allows for a more detailed solution for setting BISON boundary conditions. Furthermore, the solutions from VERA and TRACE were used to set up and perform BISON simulations of about 1,000 rods sampled from the core, including all burnup levels. Utilizing two cladding burst models, it was shown that no fuel rods were predicted to burst during the postulated LBLOCA transient. Additionally, a sensitivity study was performed by artificially increasing linear heat rate during the postulated LBLOCA to identify parameters that correlate with rod burst susceptibility. Burnup, fission gas release, and hoop strain were all found to be positively correlated with rod burst susceptibility. Small-break loss-of-coolant accident (SBLOCA) analyses were also performed; these analyses predicted cladding temperature increases that were bounded by the LBLOCA cladding temperatures for all small break sizes studied for this plant. However, future refinements to the plant response assumptions during the SBLOCA could impact the predicted cladding response. Finally, a benchmark study was performed between CTF and TRACE for LOCA conditions to better qualify CTF for BWR LOCA modeling.
Several short summaries of the work performed during this reporting period are presented. Topics discussed in this document include: (1) resilient seeded errors via simple techniques; (2) knowledge representation for engineering design; (3) analysis of faults in a multiversion software experiment; (4) implementation of parallel programming environment; (5) symbolic execution of concurrent programs; (6) two computer graphics systems for visualization of pressure distribution and convective density particles; (7) design of a source code management system; (8) vectorizing incomplete conjugate gradient on the Cyber 203/205; (9) extensions of domain testing theory and; (10) performance analyzer for the pisces system.
The topics are presented in viewgraph form and include the following: systems approach needed for nuclear thermal rocket (NTR) design optimization; generic NTR engine power balance codes; rocketdyne nuclear thermal system code; software capabilities; steady state model; NTR engine optimizer code-logic; reactor power calculation logic; sample multi-component configuration; NTR design code output; generic NTR code at Rocketdyne; Rocketdyne NTR model; and nuclear thermal rocket modeling directions.