SEARCH · Engineering Papers

Results for “logic programming”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

All sources NASA NTRS DOE OSTI

DOE OSTI2013

Hanford River Protection Project Life cycle Cost Modeling Tool to Enhance Mission Planning - 13396

The Life cycle Cost Model (LCM) Tool is an overall systems model that incorporates budget, and schedule impacts for the entire life cycle of the River Protection Project (RPP) mission, and is replacing the Hanford Tank Waste Operations Simulator (HTWOS) model as the foundation of the RPP system planning process. Currently, the DOE frequently requests HTWOS simulations of alternative technical and programmatic strategies for completing the RPP mission. Analysis of technical and programmatic changes can be performed with HTWOS; however, life cycle costs and schedules were previously generated by manual transfer of time-based data from HTWOS to Primavera P6. The LCM Tool automates the preparation of life cycle costs and schedules and is needed to provide timely turnaround capability for RPP mission alternative analyses. LCM is the simulation component of the LCM Tool. The simulation component is a replacement of the HTWOS model with new capability to support life cycle cost modeling. It is currently deployed in G22, but has been designed to work in any full object-oriented language with an extensive feature set focused on networking and cross-platform compatibility. The LCM retains existing HTWOS functionality needed to support system planning and alternatives studies going forward. In addition, it incorporates new functionality, coding improvements that streamline programming and model maintenance, and capability to input/export data to/from the LCM using the LCM Database (LCMDB). The LCM Cost/Schedule (LCMCS) contains cost and schedule data and logic. The LCMCS is used to generate life cycle costs and schedules for waste retrieval and processing scenarios. It uses time-based output data from the LCM to produce the logic ties in Primavera P6 necessary for shifting activities. The LCM Tool is evolving to address the needs of decision makers who want to understand the broad spectrum of risks facing complex organizations like DOE-RPP to understand how near-term programmatic decisions affect life cycle costs and commitments. (authors)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Dynamic Event Tree Analysis Through RAVEN

Conventional Event-Tree (ET) based methodologies are extensively used as tools to perform reliability and safety assessment of complex and critical engineering systems. One of the disadvantages of these methods is that timing/sequencing of events and system dynamics is not explicitly accounted for in the analysis. In order to overcome these limitations several techniques, also know as Dynamic Probabilistic Risk Assessment (D-PRA), have been developed. Monte-Carlo (MC) and Dynamic Event Tree (DET) are two of the most widely used D-PRA methodologies to perform safety assessment of Nuclear Power Plants (NPP). In the past two years, the Idaho National Laboratory (INL) has developed its own tool to perform Dynamic PRA: RAVEN (Reactor Analysis and Virtual control ENvironment). RAVEN has been designed in a high modular and pluggable way in order to enable easy integration of different programming languages (i.e., C++, Python) and coupling with other application including the ones based on the MOOSE framework, developed by INL as well. RAVEN performs two main tasks: 1) control logic driver for the new Thermo-Hydraulic code RELAP-7 and 2) post-processing tool. In the first task, RAVEN acts as a deterministic controller in which the set of control logic laws (user defined) monitors the RELAP-7 simulation and controls the activation of specific systems. Moreover, RAVEN also models stochastic events, such as components failures, and performs uncertainty quantification. Such stochastic modeling is employed by using both MC and DET algorithms. In the second task, RAVEN processes the large amount of data generated by RELAP-7 using data-mining based algorithms. This paper focuses on the first task and shows how it is possible to perform the analysis of dynamic stochastic systems using the newly developed RAVEN DET capability. As an example, the Dynamic PRA analysis, using Dynamic Event Tree, of a simplified pressurized water reactor for a Station Black-Out scenario is presented.

42 ENGINEERING↗

DOE OSTI2023

Enhancing Monte Carlo Workflows for Nuclear Reactor Analysis with Metamodel-Driven Modeling

Monte Carlo codes are essential components of many reactor physics simulation workflows as high-fidelity continuous-energy neutron transport solvers. Among Monte Carlo radiation transport codes, MCNP is particularly notable due to its diverse simulation capabilities, large user base, and long validation history. Despite being a powerful simulation tool, MCNP provides limited capabilities to allow automated execution, model transformation, or support for user-defined logic and abstractions that limit its compatibility with modern workflows. Here, to better integrate MCNP into a modern scientific workflow, we have developed an intuitive yet full-featured MCNP Application Program Interface (API) in Python, named MCNPy, which provides a specialized set of classes for MCNP input development. Moreover, to guarantee that our reading, writing, and modeling capabilities remain self-consistent (and to render the huge scope of the MCNP API manageable), we have adopted a strategy of model-driven software development in which a generalized model of the MCNP input format has been created. From this generalized model, or “metamodel,” problem-specific implementations such as an engine for input validation or a codebase for programmatic operations may be automatically generated. Since MCNPy primarily acts as a Python front-end to the underlying Java API that directly interfaces with the metamodel, it is intrinsically linked to the metamodel and thus remains maintainable. With MCNPy, users can programmatically read, write, and modify any syntactically valid MCNP input file regardless of its origin. These capabilities allow users to automate complicated tasks like design optimization and model translation for nuclear systems. As examples, this work demonstrates the use of MCNPy to find the critical radius of a plutonium sphere and to translate a 9000+ line MCNP input file into a corresponding OpenMC model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2013

Embedding global barrier and collective in torus network with each node combining input from receivers according to class map for output to senders

Embodiments of the invention provide a method, system and computer program product for embedding a global barrier and global interrupt network in a parallel computer system organized as a torus network. The computer system includes a multitude of nodes. In one embodiment, the method comprises taking inputs from a set of receivers of the nodes, dividing the inputs from the receivers into a plurality of classes, combining the inputs of each of the classes to obtain a result, and sending said result to a set of senders of the nodes. Embodiments of the invention provide a method, system and computer program product for embedding a collective network in a parallel computer system organized as a torus network. In one embodiment, the method comprises adding to a torus network a central collective logic to route messages among at least a group of nodes in a tree structure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Embedding global and collective in a torus network with message class map based tree path selection

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Embedding global barrier and collective in a torus network

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Optimized dispatch in a first-principles concentrating solar power production model

Not Available

Wagner, Michael J.↗

DOE OSTI2022

Flex-PCB Quench Antenna Developments at FNAL

We report flexible printed-circuit-board-based quench antenna arrays have been developed at FNAL since 2017. They proved to be low-noise, low-cost, sensitive, and non-invasive sensors for quench characterization in superconducting magnets, having the potential to extend even to quench detection. Starting with applications of small area sensors of this type, we have explored feasibility for operations at high pressure, and have invested in multi-channel quench antenna arrays covering the complete area of the innermost magnet layer of the conductor. We've also tested and optimized sensor geometry and relative orientations to increase sensitivity and spatial resolution. Beyond developments of warm and cold bore antennas, we've progressed to concepts which attach quench antennas to the conductor surfaces of accelerator magnets. Multiple programs and projects at FNAL and collaborating institutions benefited from this work already and our plans target further extensions of capabilities and applicability of these devices. In this paper we present the logic behind the development steps taken so far, status of our work and direction of near-term research on quench antennas at Fermilab.

43 PARTICLE ACCELERATORS↗

DOE OSTI2016

A new approach to entangling neutral atoms.

Our team has developed a new approach to entangling neutral atoms with a Rydberg-dressed interaction. Entangling neutral atoms is an essential key of quantum technologies such as quantum computation, many-body quantum simulation, and high-precision atomic sensors . The demonstrated Rydberg-dressed protocol involves adiabatically imposing a light shift on the ground state by coupling an excited Rydberg state with a tuned laser field. Using this technique, we have demonstrated a strong and tunable dipole - dipole interaction between two individually trapped atoms with energy shifts of order 1 MHz, which has been challenging to achieve in other protocols . During this program, we experimentally demonstrated Bell-state entanglement and the isomorphism to the Jaynes - Cumming model of a Rydberg-dressed two-atom system. Our theoretical calculations of a CPHASE quantum logic gate and arbitrary Dicke state quantum control in this system encourage further work.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Technology pathways for energy- and water-efficient controlled environment agriculture: A review of technologies, implementation pathways, and regional use cases

Controlled Environment Agriculture (CEA) offers high-yield, climate-resilient food production, but high energy and resource demands challenge its sustainability. This paper synthesizes technologies that can improve outcomes across six categories—energy, CO 2 utilization, building envelope, hardware, water, and process—plus colocation strategies. We evaluate 80 technologies and define ten implementation pathways bundling complementary technologies to reduce energy use, optimize water consumption, and minimize emissions. Regional application is demonstrated through five U.S. case studies spanning different climates. A logic framework guides pathway selection for case studies based on climate, infrastructure, and regulatory context, informing context-sensitive technology deployment. Results show energy intensity reductions of 3–55 %, ranging from energy management programs to comprehensive lighting retrofits; water savings of 20–40 % through closed-loop recirculation; and emissions reductions of 3–100 %, with strategic energy management achieving 3–5 % and renewable electricity paired with electrified heating achieving up to 100 %. Text mining revealed that energy, hardware, and process technologies account for 91 % of literature coverage. Water, building envelope, and CO 2 utilization remain underexplored, indicating priorities for future research. This integrative approach to technology assessment supports growers, developers, and policymakers in aligning CEA system design with local conditions, improving resource efficiency and addressing gaps in cross-domain technology coverage.

Controlled environment agriculture↗

DOE OSTI2021

Open Radiation Monitoring: Histogram Builder Module Design

The Open Radiation Monitoring Project seeks to develop and demonstrate a modular radiation detection architecture designed specifically for use in arms control treaty verification (ACTV) applications that will facilitate rapid development of trusted systems to meet the needs of potential future treaties. A modular architecture can be used to reduce more complex systems to a series of single purpose building blocks, thereby facilitating equipment inspection and in turn building trust in the equipment by all treaty parties. Furthermore, a modular architecture can be used to control data flow within the measurement system, reducing the risk of "hidden switches" and constraining the amount of sensitive information that could potentially be inadvertently leaked. This report details the first revision of a prototype circuit that will convert analog pulses directly into a histogrammed data set for further processing. The circuit was designed with both spectroscopy and multiplicity analysis in mind but can, in principle, be used to reduce any raw data stream into a histogram. The number of output channels is limited, and the histogram bin ranges are user configurable to allow for non-uniform and discontinuous bins, which makes it possible to restrict the information being passed down stream if desired. Pulse processing relies entirely on analog circuitry and non- programmable logic, which enables operation without the need for a central processor or other programmable control unit. The circuit remains untested under the Open Radiation Monitoring project due to the closure of the sponsoring program. However, further development and testing is scheduled to take place in support of a purpose-built trusted verification system development effort known as COGNIZANT, which demonstrates the potential benefit of developing a suite of modular trusted system components.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

SeeQ: A Programming Model for Portable Data-Driven Building Applications

This paper introduces SeeQ, a programming model and an abstraction framework that facilitates the development of portable data- driven building applications. Data-driven approaches can provide insights into building operations and guide decision-making to achieve operational objectives. Yet the configuration of such applications per building requires extensive effort and tacit knowledge. In SeeQ, we propose a portable programming model and build a software system that enables self-configuration and execution across diverse buildings. The configuration of each building is captured in a unified data model - in this paper, we work with the Brick ontology without loss of generality. SeeQ focuses on the distinction between the application logic and the configuration of an application against building-specific data inputs and systems. We test the proposed approach by configuring and deploying a diverse range of applications across five heterogeneous real-world buildings. The analysis shows the potential of SeeQ to significantly reduce the efforts associated with the delivery of building analytics.

analytics↗

DOE OSTI2022

Synthetic genetic circuits as a means of reprogramming plant roots

We report the shape of a plant’s root system influences its ability to reach essential nutrients in the soil and to acquire water during drought. Progress in engineering plant roots to optimize water and nutrient acquisition has been limited by our capacity to design and build genetic programs that alter root growth in a predictable manner. We developed a collection of synthetic transcriptional regulators for plants that can be compiled to create genetic circuits. These circuits control gene expression by performing Boolean logic operations and can be used to predictably alter root structure. This work demonstrates the potential of synthetic genetic circuits to control gene expression across tissues and reprogram plant growth.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Extending the Remote Control Capabilities in the CMS Detector Control System with Remote Procedure Call Services

The CMS Detector Control System (DCS) is implemented as a large distributed and redundant system, with applications interacting and sharing data in multiple ways. The CMS XML-RPC is a software toolkit implementing the standard Remote Procedure Call (RPC) protocol, using the Extensible Mark-up Language (XML) and a custom lightweight variant using the JavaScript Object Notation (JSON) to model, encode and expose resources through the Hypertext Transfer Protocol (HTTP). The CMS XML-RPC toolkit complies with the standard specification of the XML-RPC protocol that allows system developers to build collaborative software architectures with self-contained and reusable logic, and with encapsulation of well-defined processes. The implementation of this protocol introduces not only a powerful communication method to operate and exchange data with web-based applications, but also a new programming paradigm to design service-oriented software architectures within the CMS DCS domain. This paper presents details of the CMS XML-RPC implementation in WinCC Open Architecture (OA) Control Language using an object-oriented approach.

43 PARTICLE ACCELERATORS↗

DOE OSTI2016

Utilizing Genetic Programming to Identify Failures in ICS Networks

Previously, researchers have attempted to apply machine learning techniques to network anomaly detection problems. Due to the staggering amount of variety that can occur in normal networks, the results have often been underwhelming. These challenges are far less pronounced when considering industrial control system (ICS) networks. The recurrent nature of these networks results in less noise and more consistent patterns for a machine learning algorithm to recognize. Here, we propose a method of evolving decision trees through genetic programming (GP) in order to detect network anomalies, such as device outages. Our approach extracts over a dozen features from network packet captures and netflows, normalizes them, and relates them in decision trees using fuzzy logic operators. Furthermore, the trees were used to detect three specific network events from three different points on the network across a statistically significant number of runs and achieved 100% accuracy on five of the nine experiments. When the trees attempted to detect more challenging events at points of presence further from the occurrence, the accuracy averaged to above 98%. Finally, using our method, all of the evolutionary cycles of the GP algorithm are computed a-priori, allowing the best resultant trees to be deployed as semi-real-time sensors with little overhead.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Incorporating FLEX Strategies in Multi-Unit Probabilistic Risk Assessment

The catastrophic Fukushima nuclear accident reminded nuclear community about the possibilities of extreme accident scenarios, including those involving multiple reactor units on the same site. As the responses to the Fukushima accident, the nuclear power industry developed and implemented a series of strategies, including the Diverse and Flexible Coping Strategies (FLEX), to enhance the coping capacities of nuclear power plants (NPPs) under extreme accidents. This study intends to examine the impact of FLEX strategies on the risk from all the reactor units on the same NPP site, including risks from accidents involving a single unit and from accidents involving multiple units. The fundamental, methodological element of this study is Multi-Unit Probabilistic Risk Assessment (MUPRA), which requires a shift in Probabilistic Risk Assessment (PRA) from a “one-reactor-at-a-time” mindset to a “considering all reactors sharing a site as a unity” one. An integrated modeling approach for multi-unit event sequence development will be leveraged to develop MUPRA model and address the intra-unit and inter-unit dependencies. Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE), a PRA software developed and maintained by Idaho National Laboratory (INL) for the U.S. Nuclear Regulatory Commission (NRC), will serve as the platform for MUPRA modeling. This study selects Loss Of Offsite Power (LOOP) as a representative initiating event, which may occur on a generic two-unit NPP site and impacts both reactor units on the site. First, an MUPRA model, including multi-unit event trees, will be developed to obtain single-unit and multi-unit accident scenarios. Next, different FLEX strategies will be assumed, including FLEX equipment for a unit cannot be used for another unit, FLEX equipment for multiple units can be used in a cross-connected manner, etc. Lastly, the effectiveness of each postulated FLEX strategy will be evaluated by incorporating the corresponding FLEX equipment and deployment logic in the MUPRA model.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Parthenon—a performance portable block-structured adaptive mesh refinement framework

On the path to exascale the landscape of computer device architectures and corresponding programming models has become much more diverse. While various low-level performance portable programming models are available, support at the application level lacks behind. To address this issue, we present the performance portable block-structured adaptive mesh refinement (AMR) framework Parthenon, derived from the well-tested and widely used Athena++ astrophysical magnetohydrodynamics code, but generalized to serve as the foundation for a variety of downstream multi-physics codes. Parthenon adopts the Kokkos programming model, and provides various levels of abstractions from multidimensional variables, to packages defining and separating components, to launching of parallel compute kernels. Parthenon allocates all data in device memory to reduce data movement, supports the logical packing of variables and mesh blocks to reduce kernel launch overhead, and employs one-sided, asynchronous MPI calls to reduce communication overhead in multi-node simulations. Using a hydrodynamics miniapp, we demonstrate weak and strong scaling on various architectures including AMD and NVIDIA GPUs, Intel and AMD x86 CPUs, IBM Power9 CPUs, as well as Fujitsu A64FX CPUs. At the largest scale on Frontier (the first TOP500 exascale machine), the miniapp reaches a total of 1.7 × 10 13 zone-cycles/s on 9216 nodes (73,728 logical GPUs) at [Formula: see text] weak scaling parallel efficiency (starting from a single node). In combination with being an open, collaborative project, this makes Parthenon an ideal framework to target exascale simulations in which the downstream developers can focus on their specific application rather than on the complexity of handling massively-parallel, device-accelerated AMR.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Demonstrating Load-Shaping Capabilities of Cost Minimizing Heat Pump Water Heater Controls with Varying Price Profiles

Increased penetration of photovoltaics and electrification of traditionally gas appliances are exacerbating existing challenges in cost-effectively balancing electricity grid supply and demand. Decarbonization without incurring expensive transmission and distribution system capacity increases requires shifting building loads from peak demand times to peak renewable production times. Grid operators are evaluating new ways of encouraging load shifting, including using time-varying price structures to provide a financial incentive. If devices incorporate price-responsive controls, a price profile could be designed to yield a wide variety of load curves as needed to optimize grid functionality. Heat pump water heaters (HPWHs) are an ideal device for price-responsive controls because the storage tank enables them to optimize the timing of electricity consumption without impacting hot water delivery service. This paper presents work demonstrating how price-responsive controls for HPWHs can provide different load profiles, as needed to stabilize the grid, in response to different price profiles. HPWH manufacturers now include web API and CTA-2045 communication capabilities which enable sending load shaping control signals. Pilot studies and preliminary programs have utilized these capabilities with uniform control strategies to reduce 4-9 PM electricity consumption. However, no studies have developed flexible controls capable of both a) responding to constantly varying price profiles and b) customizing logic to match the needs of each HPWH. Berkeley Lab's CalFlexHub project is pioneering price-driven load flexibility by developing and deploying cost-minimizing controls utilizing setpoint setting signals for fleets of HPWHs in response to varying price profiles. Control development is based on simulations using the Flexible Heat Pump Water Heater Performance Predictor which captures the control decisions of a residential, integrated HPWH manufacturer’s on-board controller. The proposed cost-reducing controls respond to constantly changing price profiles, providing the ability to change the price profile to generate load curves as needed to maintain grid stability. Preliminary simulations studying the load shaping capabilities of price-responsive controls on a fleet of 60 HPWHs have demonstrated an average of a) 135.4% increases in load during low-price periods, b) >36.8% reductions in electricity peak-price period, and c) 6.2% electricity cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗