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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Blackcomb: Hardware-Software Co-design for Non-Volatile Memory in Exascale Systems

Summary of technical results of Blackcomb Memory Devices We explored various different memory technologies (STTRAM, PCRAM, FeRAM, and ReRAM). The progress can be classified into three categories, below. Modeling and Tool Releases Various modeling tools have been developed over the last decade to help in the design of SRAM or DRAM-based memory hierarchies. To explore new design opportunities that NVM technologies can bring to the designers, we have developed similar high-level models for NVM, including PCRAMsim [Dong 2009], NVSim [Dong 2012], and NVMain [Poremba 2012]. NVSim is a circuit-level model for NVM performance, energy, and area estimation, which supports various NVM technologies, including STT-RAM, PCRAM, ReRAM, and legacy NAND Flash. NVSim is successfully validated against industrial NVM prototypes, and it is expected to help boost architecture-level NVM-related studies. On the other side, NVMain is a cycle accurate main memory simulator designed to simulate emerging nonvolatile memories at the architectural level. We have released these models as open source tools and provided contiguous support to them. We also proposed PS3-RAM, which is a fast, portable and scalable statistical STT-RAM reliability analysis model [Wen 2012]. Design Space Exploration and Optimization With the support of these models, we explore different device/circuit optimization techniques. For example, in [Niu 2012a] we studied the power reduction technique for the application of ECC scheme in ReRAM designs and proposed to use ECC code to relax the BER (Bit Error Rate) requirement of a single memory to improve the write energy consumption and latency for both 1T1R and cross-point ReRAM designs. In [Xu 2011], we proposed a methodology to design STT-RAM for different optimization goals such as read performance, write performance and write energy by leveraging the trade-off between write current and write time of MTJ. We also studied the tradeoffs in building a reliable crosspoint ReRAM array [Niu 2012b]. We have conducted an in depth analysis of the circuit and system level design implications of multi-layer cross-point Resistive RAM (MLCReRAM) from performance, power and reliability perspectives [Xu 2013]. The objective of this study is to understand the design trade-offs of this technology with respect to the MLC Phase Change Memory (MLCPCM).Our MLC ReRAM design at the circuit and system levels indicates that different resistance allocation schemes, programming strategies, peripheral designs, and material selections profoundly affect the area, latency, power, and reliability of MLC ReRAM. Based on this analysis, we conduct two case studies: first we compare MLC ReRAM design against MLC phase-change memory (PCM) and multi-layer cross-point ReRAM design, and point out why multi-level ReRAM is appealing; second we further explore the design space for MLC ReRAM. Architecture and Application We explored hybrid checkpointing using phase-change memory for future exascale systems [Dong 2011] and showed that the use of nonvolatile memory for local checkpointing significantly increases the number of faults covered by local checkpoints and reduces the probability of a global failure in the middle of a global checkpoint to less than 1%. We also proposed a technique called i2WAP to mitigate the write variations in NVM-based last-level cache for the improvement of the NVM lifetime [Wang 2013]. Our wear leveling technique attempts to work around the limitations of write endurance by arranging data access so that write operations can be distributed evenly across all the storage cells. During our intensive research on fault-tolerant NVM design, we found that ECC cannot effectively tolerate hard errors from limited write endurance and process imperfection. Therefore, we devised a novel Point and Discard (PAD) architecture in in [ 2012] as a hard-error-tolerant architecture for ReRAM-based Last Level Caches. PAD improves the lifetime of ReRAM caches by 1.6X-440X under different process variations without performance overhead in the system's early life. We have investigated the applicability of NVM for persistent memory design [Zhao 2013]. New byte addressable NVM enables fast persistent memory that allows in-memory persistent data objects to be updated with much higher throughput. Despite the significant improvement, the performance of these designs is only 50% of the native system with no persistence support, due to the logging or copy-on-write mechanisms used to update the persistent memory. A challenge in this approach is therefore how to efficiently enable atomic, consistent, and durable updates to ensure data persistence that survives application and/or system failures. We have designed a persistent memory system, called Klin, that can provide performance as close as that of the native system. The Klin design adopts a non-volatile cache and a non-volatile main memory for constructing a multi-versioned durable memory system, enabling atomic updates without logging or copy-on-write. Our evaluation shows that the proposed Kiln mechanism can achieve up to 2X of performance improvement to NVRAM-based persistent memory employing write-ahead logging. In addition, our design has numerous practical advantages: a simple and intuitive abstract interface, microarchitecture-level optimizations, fast recovery from failures, and no redundant writes to slow non-volatile storage media. The work was published in MICRO 2013 and received Best Paper Honorable Mentioned Award.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Monte Carlo Uncertainty Quantification for an Unattended Enrichment Monitor

As a case study for uncertainty analysis, we consider a model flow monitor for measuring enrichment in gas centrifuge enrichment plants (GCEPs) that could provide continuous monitoring of all declared gas flow and provide high-accuracy gas enrichment estimates as a function of time. The monitor system could include NaI(Tl) gamma-ray spectrometers, a pressure signal-sharing device to be installed on an operator\rq{}s pressure gauge or a dedicated inspector pressure sensor, and temperature sensors attached to the outside of the header pipe, to provide pressure, temperature, and gamma-ray spectra measurements of UF$_6$ gas flow through unit header pipes. Our study builds on previous modeling and analysis methods development for enrichment monitor concepts and a software tool that was developed at Oak Ridge National Laboratory to generate and analyze synthetic data.

international safeguards↗
DOE OSTI2015

Electrostatics on the sphere with applications to Monte Carlo simulations of two dimensional polar fluids

We present two methods for solving the electrostatics of point charges and multipoles on the surface of a sphere, i.e., in the space S{sub 2}, with applications to numerical simulations of two-dimensional (2D) polar fluids. In the first approach, point charges are associated with uniform neutralizing backgrounds to form neutral pseudo-charges, while in the second, one instead considers bi-charges, i.e., dumbells of antipodal point charges of opposite signs. We establish the expressions of the electric potentials of pseudo- and bi-charges as isotropic solutions of the Laplace-Beltrami equation in S{sub 2}. A multipolar expansion of pseudo- and bi-charge potentials leads to the electric potentials of mono- and bi-multipoles, respectively. These potentials constitute non-isotropic solutions of the Laplace-Beltrami equation, the general solution of which in spherical coordinates is recast under a new appealing form. We then focus on the case of mono- and bi-dipoles and build the theory of dielectric media in S{sub 2}. We notably obtain the expression of the static dielectric constant of a uniform isotropic polar fluid living in S{sub 2} in terms of the polarization fluctuations of subdomains of S{sub 2}. We also derive the long range behavior of the equilibrium pair correlation function under the assumption that it is governed by macroscopic electrostatics. These theoretical developments find their application in Monte Carlo simulations of the 2D fluid of dipolar hard spheres. Some preliminary numerical experiments are discussed with a special emphasis on finite size effects, a careful study of the thermodynamic limit, and a check of the theoretical predictions for the asymptotic behavior of the pair correlation function.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

TU-AB-BRC-11: Moving a GPU-OpenCL-Based Monte Carlo (MC) Dose Engine Towards Routine Clinical Use: Automatic Beam Commissioning and Efficient Source Sampling

Purpose: We have previously developed a GPU-OpenCL-based MC dose engine named goMC with built-in analytical linac beam model. To move goMC towards routine clinical use, we have developed an automatic beam-commissioning method, and an efficient source sampling strategy to facilitate dose calculations for real treatment plans. Methods: Our commissioning method is to automatically adjust the relative weights among the sub-sources, through an optimization process minimizing the discrepancies between calculated dose and measurements. Six models built for Varian Truebeam linac photon beams (6MV, 10MV, 15MV, 18MV, 6MVFFF, 10MVFFF) were commissioned using measurement data acquired at our institution. To facilitate dose calculations for real treatment plans, we employed inverse sampling method to efficiently incorporate MLC leaf-sequencing into source sampling. Specifically, instead of sampling source particles control-point by control-point and rejecting the particles blocked by MLC, we assigned a control-point index to each sampled source particle, according to MLC leaf-open duration of each control-point at the pixel where the particle intersects the iso-center plane. Results: Our auto-commissioning method decreased distance-to-agreement (DTA) of depth dose at build-up regions by 36.2% averagely, making it within 1mm. Lateral profiles were better matched for all beams, with biggest improvement found at 15MV for which root-mean-square difference was reduced from 1.44% to 0.50%. Maximum differences of output factors were reduced to less than 0.7% for all beams, with largest decrease being from1.70% to 0.37% found at 10FFF. Our new sampling strategy was tested on a Head&Neck VMAT patient case. Achieving clinically acceptable accuracy, the new strategy could reduce the required history number by a factor of ∼2.8 given a statistical uncertainty level and hence achieve a similar speed-up factor. Conclusion: Our studies have demonstrated the feasibility and effectiveness of our auto-commissioning approach and new efficient source sampling strategy, implying the potential of our GPU-based MC dose engine goMC for routine clinical use.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2006

What Do Our Users Want? Perspectives on Understanding and Meeting User Needs for Multi-Mission Data Services

The Sun-Earth Connection Active Archive (SECAA) project of NASA's Space Physics Data Facility operates a range of unique and heavily used multi-mission data services in support of the large-scale science objectives of the Great Observatory, including services such as CDAWeb, the CDAWeb Plus client, SSCWeb, OMNIweb and the CDF data format. In developing and operating these services, we have encountered and continue to struggle with a wide range of issues such as balancing scope and functionality with simplicity and ease of use, understanding the effectiveness of our choices and identifying areas most important for further improvement. In this paper, we will review our key services and then discuss some of our observations and new approaches to understanding and meeting user data service requirements. Some observations are obvious but may still have substantial implications; e.g. functionality without information content is of little user interest, which has led to our recent emphasis on development of web services interfaces, so the content and functionality we already serve is readily and fully available as a building block for new services. Some observations require careful design and tradeoffs; e.g. users will complain when they are offered interfaces with limited options but users are also easily intimidated and become lost when offered extensive options for customization. Some observations remain highly challenging; e.g. a comprehensive multi-mission, multi-source view of all data and services available easily produces a daunting list, but a more selective view can easily lead users to overlook available and relevant data. It is often difficult to obtain and meaningfully interpret measures of true productive usage and overall user satisfaction, even with a variety of techniques including statistics, citations, case studies, user feedback and advisory committees. Most of these issues will apply to and may even be more acute for distributed implementation architectures.

McGuire, Robert E.↗
NASA NTRS2018

Modeling Principles Using the Relation Between Lagrange Multipliers and Bond Graphs

Final document is attached. Modeling dynamic systems by bond graphs has become state of the art technology since hundreds of researchers around the world have incorporated the technology in many fields of engineering and science. The legacy of its invertor Prof. Henry Paynter at MIT in 1959 is now a fundamental and practical technique to understand reality by building computer models. This paper addresses a particular aspect of this technology when modeling of mechanical systems require relaxation of constraints by means of Lagrange principles. Lagrange's equations are a useful means of describing and solving systems with kinematic constraints. Lagrange multipliers are variables used in equations to find the extremes of multivariate functions. Here we explore the relation of Lagrange multipliers to solve modeling difficulties of a space vehicle with equations with dependent derivatives. Lagrange multipliers were used in conjunction with bond graphs to simulate a system where joints of kinematic linkages produce dependent derivatives. NASA's Morpheus Project lunar lander was used as a case study. The Morpheus Project is a terrestrial test vehicle designed to fly the terminal descent trajectory of a lunar lander to advance the Autonomous Landing Hazard Avoidance Technology (ALHAT). An objective of this study is to apply the modeling approach herein to capture the dynamic movement of the lander as the propellant is sloshed and consumed. This paper expands further the analysis presented by (Granda, J J. Nguyen, L, Carlson, T, Sahragard-Monfared, G., Fornalski, E., Brocker 2016). Using an automated approach bond graph models of state space equations were generated using the Computer Aided Modeling Program (CAMPG). Integral causality models and derivative causality models were considered in order to find the simpler solution for the mathematical dependencies produced in modeling this vehicle.

Granda, Jose J.↗
NASA NTRS2021

Mapping the Extent of Mangrove Ecosystem Degradation by Integrating an Ecological Conceptual Model with Satellite Data

Anthropogenic and natural disturbances can cause degradation of ecosystems, reducing their capacity to sustain biodiversity and provide ecosystem services. Understanding the extent of ecosystem degradation is critical for estimating risks to ecosystems, yet there are few existing methods to map degradation at the ecosystem scale and none using freely available satellite data for mangrove ecosystems. In this study, we developed a quantitative classification model of mangrove ecosystem degradation using freely available earth observation data. Crucially, a conceptual model of mangrove ecosystem degradation was established to identify suitable remote sensing variables that support the quantitative classification model, bridging the gap between satellite-derived variables and ecosystem degradation with explicit ecological links. We applied our degradation model to two case-studies, the mangroves of Rakhine State, Myanmar, which are severely threatened by anthropogenic disturbances, and Shark River within the Everglades National Park, USA, which is periodically disturbed by severe tropical storms. Our model suggested that 40% (597 km2) of the extent of mangroves in Rakhine showed evidence of degradation. In the Everglades, the model suggested that the extent of degraded mangrove forest increased from 5.1% to 97.4% following the Category 4 Hurricane Irma in 2017. Quantitative accuracy assessments indicated the model achieved overall accuracies of 77.6% and 79.1% for the Rakhine and the Everglades, respectively. We highlight that using an ecological conceptual model as the basis for building quantitative classification models to estimate the extent of ecosystem degradation ensures the ecological relevance of the classification models. Our developed method enables researchers to move beyond only mapping ecosystem distribution to condition and degradation as well. These results can help support ecosystem risk assessments, natural capital accounting, and restoration planning and provide quantitative estimates of ecosystem degradation for new global biodiversity targets.

Calvin K. F. Lee↗
DOE OSTI2018

Misleading or Falsification? Inferring Deceptive Strategies and Types in Online News and Social Media

Deceptive information in online news and social media has had dramatic effect on our society in recent years. This study is the first to gain deeper insights into writers' intent behind digital misinformation by analyzing psycholinguistic signals: moral foundations and connotations extracted from different types of deceptive news ranging from strategic disinformation to propaganda and hoaxes. To ensure consistency of our findings and generalizability across domains, we experiment with data from: (1) confirmed cases of disinformation in news summaries, (2) {propaganda}, hoax, and disinformation news pages, and (3) social media news. We first contrast lexical markers of biased language, syntactic and stylistic signals, and connotations across deceptive news types including disinformation, propaganda, and hoaxes, and {deceptive} strategies including misleading or falsification. We then incorporate these insights to build machine learning and deep learning predictive models to infer deception strategies and deceptive news types. Our experimental results demonstrate that unlike earlier work on deception detection, content combined with biased language markers, moral foundations, and connotations leads to better predictive performance of deception strategies compared to syntactic and stylistic signals (as reported in earlier work on deceptive reviews). Falsification strategy is easier to identify than misleading strategy. Disinformation is more difficult to predict than to propaganda or hoaxes. Deceptive news types (disinformation, propaganda, and hoaxes), unlike deceptive strategies (falsification and misleading), are more salient, and thus easier to identify in tweets than in news reports. Finally, our novel connotation analysis across deception types provides deeper understanding of writers' perspectives and therefore reveals the intentions behind digital misinformation.

deception↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Approximate Inverse Chain Preconditioner: Iteration Count Case Study for Spectral Support Solvers

As the growing availability of computational power slows, there has been an increasing reliance on algorithmic advances. However, faster algorithms alone will not necessarily bridge the gap in allowing computational scientists to study problems at the edge of scientific discovery in the next several decades. Often, it is necessary to simplify or precondition solvers to accelerate the study of large systems of linear equations commonly seen in a number of scientific fields. Preconditioning a problem to increase efficiency is often seen as the best approach; yet, preconditioners which are fast, smart, and efficient do not always exist. Following the progress of [1], we present a new preconditioner for symmetric diagonally dominant (SDD) systems of linear equations. These systems are common in certain PDEs, network science, and supervised learning among others. Based on spectral support graph theory, this new preconditioner builds off of the work of [2], computing and applying a V-cycle chain of approximate inverse matrices. This preconditioner approach is both algebraic in nature as well as hierarchically-constrained depending on the condition number of the system to be solved. Due to its generation of an Approximate Inverse Chain of matrices, we refer to this as the AIC preconditioner. We further accelerate the AIC preconditioner by utilizing precomputations to simplify setup and multiplications in the con-text of an iterative Krylov-subspace solver. While these iterative solvers can greatly reduce solution time, the number of iterations can grow large quickly in the absence of good preconditioners. Initial results for the AIC preconditioner have shown a very large reduction in iteration counts for SDD systems as compared to standard preconditioners such as Incomplete Cholesky (ICC) and Multigrid (MG). We further show significant reduction in iteration counts against the more advanced Combinatorial Multigrid (CMG) preconditioner. We have further developed no-fill sparsification techniques to ensure that the computational cost of applying the AIC preconditioner does not grow prohibitively large as the depth of the V-cycle grows for systems with larger condition numbers. Our numerical results have shown that these sparsifiers maintain the sparsity structure of our system while also displaying significant reductions in iteration counts.1 2

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Interaction between laser radiation and metallic powder of 316L austenitic steel during selective laser melting

Highlights: • Single and multiple tracks on a loose bulk powder substrate were generated. • Understanding of the microstructure development during SLM was achieved. • Single tracks reveal a nearly symmetrical crystallography with elongated grains. • Multiple tracks show elongated grains perpendicular to the build direction. - Abstract: During selective laser melting (SLM), a complex heat state develops that leads to a characteristic crystallography and microstructure of the processed materials. Depending on the geometry of the processed part, most scan tracks of a new layer, so-called hatches, are located above a dense substrate or already solidified structures whereas others are located above loose powder. This is, inter alia, the case for overhanging structures. Attributable to the lower thermal conductivity of loose powder, temperature gradients and cooling rates of the melt pool differentiate in these areas, resulting in a different microstructural build-up. In this work, the microstructure and the crystallographic orientation of grade 316L austenitic stainless steel processed by SLM was investigated to understand the interaction between the laser radiation and the metallic powder during SLM-processing and to investigate the remelting of a track on a previous SLM-densified track. Single and multiple tracks on a loose bulk powder substrate, as well as single tracks on a dense substrate plate, were generated. A parameter study revealed that high energy densities are necessary to build continuous tracks on a loose bulk powder substrate. In addition, the amount of adhered particles, which are sintered on the fully melted and solidified tracks, is determined in comparison to the melted powder because the sintered particles strongly influence the surface roughness. To understand the microstructure development and, particularly, the influence of adjacent hatches during SLM-processing, investigations on the resulting microstructure and crystallographic orientation of a single track and two connected multiple tracks were carried out. During SLM processing of the tracks, the substrate plate and the solidified structures influence the temperature gradient and cooling rate of the melt pool, thus directionally solidified and elongated grains occur. Furthermore, the solidification is characterized by an epitaxial growth due to a distinct thermal gradient between the melt pool and the surrounding elements.

36 MATERIALS SCIENCE↗
DOE OSTI2014

DOE Zero Energy Ready Home Case Study: Near Zero Maine Home II - Vassalboro, Maine

This case study describes a DOE Zero Energy Ready home in Vassalboro, Maine, that scored HERS 35 without PV and HERS 11 with PV. This 1,200 ft2 home has 10.5-inch-thick double-walls with 3 layers of mineral wool batt insulation, an R-20 insulated slab, R-70 cellulose in the attic, extensive air sealing, a mini-split heat pump, an heat recovery ventilator, solar water heating, LED lighting, 3.9 kWh PV, and triple-pane windows.

builder↗
DOE OSTI2013

Application of Spray Foam Insulation Under Plywood and Oriented Strand Board Roof Sheathing

Unvented roof strategies with open cell and closed cell spray polyurethane foam insulation sprayed to the underside of roof sheathing have been used since the mid-1990's to provide durable and efficient building enclosures. However, there have been isolated moisture related incidents reported anecdotally that raise potential concerns about the overall hygrothermal performance of these systems. The incidents related to rainwater leakage and condensation concerns. Condensation concerns have been extensively studied by others and are not further discussed in this report. This project involved hygrothermal modeling of a range of rainwater leakage and field evaluations of in-service residential roofs using spray foam insulation. All of the roof assemblies modeled exhibited drying capacity to handle minor rainwater leakage. All field evaluation locations of in-service residential roofs had moisture contents well within the safe range for wood-based sheathing. Explorations of eleven in-service roof systems were completed. The exploration involved taking a sample of spray foam from the underside of the roof sheathing, exposing the sheathing, then taking a moisture content reading. All locations had moisture contents well within the safe range for wood-based sheathing. One full-roof failure was reviewed, as an industry partner was involved with replacing structurally failed roof sheathing. In this case the manufacturer's investigation report concluded that the spray foam was installed on wet OSB based on the observation that the spray foam did not adhere well to the substrate and the pore structure of the closed cell spray foam at the ccSPF/OSB interface was indicative of a wet substrate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

A conceptual framework for negotiating public involvement in municipal waste management decision-making in the UK

Highlights: • A review of public involvement in waste management decision-making was undertaken. • Public involvement seen as necessary to create stronger foundations for decisions. • The mode and level of public involvement explored in different decision contexts. • Public involvement can be negotiated based on the technological and social context. • Early public involvement favoured where issues are contentious or uncertain. - Abstract: The technical expertise that politicians relied on in the past to produce cost-effective and environmentally sound solutions no longer provides sufficient justification to approve waste facilities. Local authorities need to find more effective ways to involve stakeholders and communities in decision-making since public acceptance of municipal waste facilities is integral to delivering effective waste strategies. This paper presents findings from a research project that explored attitudes towards greater levels of public involvement in UK waste management decision-making. The study addressed questions of perception, interests, the decision context, the means of engagement and the necessary resources and capacity for adopting a participatory decision process. Adopting a mixed methods approach, the research produced an empirical framework for negotiating the mode and level of public involvement in waste management decision-making. The framework captures and builds on theories of public involvement and the experiences of practitioners, and offers guidance for integrating analysis and deliberation with public groups in different waste management decision contexts. Principles in the framework operate on the premise that the decision about ‘more’ and ‘better’ forms of public involvement can be negotiated, based on the nature of the waste problem and wider social context of decision-making. The collection of opinions from the wide range of stakeholders involved in the study has produced new insights for the design of public engagement processes that are context-dependent and ‘fit-for-purpose’; these suggest a need for greater inclusivity in the case of contentious technologies and high levels of uncertainty regarding decision outcomes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein–protein interaction network

Abstract Although drug combinations in cancer treatment appear to be a promising therapeutic strategy with respect to monotherapy, it is arduous to discover new synergistic drug combinations due to the combinatorial explosion. Deep learning technology holds immense promise for better prediction of in vitro synergistic drug combinations for certain cell lines. In methods applying such technology, omics data are widely adopted to construct cell line features. However, biological network data are rarely considered yet, which is worthy of in-depth study. In this study, we propose a novel deep learning method, termed PRODeepSyn, for predicting anticancer synergistic drug combinations. By leveraging the Graph Convolutional Network, PRODeepSyn integrates the protein–protein interaction (PPI) network with omics data to construct low-dimensional dense embeddings for cell lines. PRODeepSyn then builds a deep neural network with the Batch Normalization mechanism to predict synergy scores using the cell line embeddings and drug features. PRODeepSyn achieves the lowest root mean square error of 15.08 and the highest Pearson correlation coefficient of 0.75, outperforming two deep learning methods and four machine learning methods. On the classification task, PRODeepSyn achieves an area under the receiver operator characteristics curve of 0.90, an area under the precision–recall curve of 0.63 and a Cohen’s Kappa of 0.53. In the ablation study, we find that using the multi-omics data and the integrated PPI network’s information both can improve the prediction results. Additionally, the case study demonstrates the consistency between PRODeepSyn and previous studies.

Wang, Xiaowen↗
DOE OSTI2019

Studying Qubit Interactions with Multimode Cavities Using QuTiP

The project uses QuTiP, a quantum computing framework [1], to simulate interactions between two-qubits coupled with each other via three resonators. The main aim of this project is to build a machinery of techniques to understand complex qubit-cavity interactions using QuTiP’s functionalities. The system simulated mimics the one constructed by McKay et. al. [2] (M15) and the results of the simulations closely agree with M15’s experimental results. The effect of the coupling strength between the qubits and the cavities is studied. It was observed that stronger couplings generated larger separations between the eigen-modes. Studies involving resonance were used to construct the iSWAP gate, a universal quantum logic gate. This study showed the importance of external thermal losses due to cavity dissipation, and qubit decay and dephasing. The Landau-Zener model was tested for the case of multiple crossing; the model motivated the comparison of three scenarios where the 2 qubits were coupled via: 1 cavity, 3 cavities, and 6 cavities. The study concluded that having multiple modes, which is a consequence of having multiple cavities, is advantageous for transferring energy from the qubit to the cavity. Finally, the ac-Stark shift was measured in the system and it’s dynamics showed excellent agreement with the experimental results obtained by M15.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Simplifications for hydronic system models in modelica

Building systems and their heating, ventilation and air conditioning flow networks, are becoming increasingly complex. Some building energy simulation tools simulate these flow networks using pressure drop equations. These flow network models typically generate coupled algebraic nonlinear systems of equations, which become increasingly more difficult to solve as their sizes increase. This leads to longer computation times and can cause the solver to fail. These problems also arise when using the equation-based modelling language Modelica and Annex 60-based libraries. This may limit the applicability of the library to relatively small problems unless problems are restructured. This paper discusses two algebraic loop types and presents an approach that decouples algebraic loops into smaller parts, or removes them completely. The approach is applied to a case study model where an algebraic loop of 86 iteration variables is decoupled into smaller parts with a maximum of five iteration variables.

42 ENGINEERING↗
DOE OSTI2013

High intensity neutrino oscillation facilities in Europe

The EUROnu project has studied three possible options for future, high intensity neutrino oscillation facilities in Europe. The first is a Super Beam, in which the neutrinos come from the decay of pions created by bombarding targets with a 4 MW proton beam from the CERN High Power Superconducting Proton Linac. The far detector for this facility is the 500 kt MEMPHYS water Cherenkov, located in the Fréjus tunnel. The second facility is the Neutrino Factory, in which the neutrinos come from the decay of μ + and μ – beams in a storage ring. The far detector in this case is a 100 kt magnetized iron neutrino detector at a baseline of 2000 km. The third option is a Beta Beam, in which the neutrinos come from the decay of beta emitting isotopes, in particular 6 He and 18 Ne, also stored in a ring. The far detector is also the MEMPHYS detector in the Fréjus tunnel. EUROnu has undertaken conceptual designs of these facilities and studied the performance of the detectors. Based on this, it has determined the physics reach of each facility, in particular for the measurement of CP violation in the lepton sector, and estimated the cost of construction. These have demonstrated that the best facility to build is the Neutrino Factory. Furthermore, if a powerful proton driver is constructed for another purpose or if the MEMPHYS detector is built for astroparticle physics, the Super Beam also becomes very attractive.

43 PARTICLE ACCELERATORS↗