Results for “statistically designed experiments” — Page 8

DOE OSTI2016

Probing Flavor Asymmetry of Anti-quarks in the Proton by Drell-Yan Experiment SeaQuest

A new measurement on the avor asymmetry between d and u in the proton is reported in this thesis. The proton contains a substantial number of antiquarks which arise from dynamical interactions of gluons such as gluon dissociation to a quark-antiquark pair, g ! q + q, and from non-perturbative processes as described by the pion-cloud model, for example. The antiquarks in the proton undertake an important role in determining the dynamic characteristics of the internal structure of the proton, although its distribution in the proton and its origin are not fully understood. Understanding sea quarks in hadron is an important subject for QCD. The SeaQuest experiment at Fermi National Accelerator Laboratory (Fermilab) is a xed target experiment using the 120 GeV proton beam extracted from the Fermilab Main Injector. One of the goals of the experiment is to measure the avor asymmetry between d quark and u quark in the proton as a function of the target Bjorken x using the Drell-Yan process in the p-p or p-d reactions. This process takes place in hadron-hadron collisions when a quark in one hadron in the beam and an antiquark in other hadron in the target annihilate into a virtual photon that decays into a lepton pair. The avor asymmetry between d and u quarks was found by deep-inelastic scattering experiment NMC at CERN. The E866/NuSea experiment at Fermilab obtained the avor asymmetry in the proton for 0:015 < x < 0:35 using the 800 GeV proton beam extracted from the Fermilab Tevatron. The result indicates the dominance of d; it is 70% larger than u at lower x. The SeaQuest experiment was planned to do a new precise measurement at higher x region. The lower energy beam (120 GeV) increases the Drell-Yan cross section and suppresses the background primarily arising from J/ decays. Therefore, SeaQuest will obtain more statistics in a shorter time than the E866 experiment. After detector construction, detector commissioning and accelerator upgrade, physics data taking started in 2013. The SeaQuest spectrometer is designed to detect dimuon from the Drell-Yan process. It consists of targets, two di-pole magnets, and four tracking detector groups. The third tracking detector group has two drift chambers. One was newly fabricated in Japan by the Japanese group in SeaQuest collaboration and was shipped to Fermilab. The other one was constructed by SeaQuest collaborator in Fermilab under the initiative of the Japanese group. I worked on the construction and installation of the detectors, data taking and data analysis in SeaQuest. I extracted the avor asymmetry as a function of Bjorken x using the SeaQuest data for the rst time. This thesis shows the results using a part of data taken in 2014 and 2015. The asymmetry was extracted for much wider Bjorken x region than the previous experiment. The measured Bjorken x range covers up to 0.58. The result shows that the ratio of d=u is always higher than 1 at 0:1 < x < 0:45, in contrast to the E866 result. For 0:45 < x < 0:58, the result shows that the ratio is close to unity. Predictions made by current PDF parameterizations are in agreement with the present result. Also, a prediction obtained by one of the non-perturbative models, pion-cloud model, is closer to the SeaQuest result than the E866 result. This result of d=u asymmetry at the wide Bjorken x region, 0:1 < x < 0:58, is very important information to understand the inner structure of the proton and the origin of the sea quarks in the proton.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2013

Use of Covariances in a Consistent Data Assimilation for Improvement of Basic Nuclear Parameters in Nuclear Reactor Applications: From Meters to Femtometers

Recognition of the key role physics plays in innovative reactor design was already made clear by E. Wigner in his warning: “It has been a bit forgotten that in all really creative thinking in reactor design, a working knowledge of nuclear reaction theory is required.” More recently, extensive sensitivity and uncertainty studies and the availability of new covariance data have allowed preliminary quantification of the impact of current nuclear data uncertainties on the design parameters of the Generation-IV systems (both fast neutron and thermal neutron systems). Similar quantifications can be done for the parameters that characterize the associated innovative fuel cycle to insure sustainability, waste minimization and drastic reduction of the proliferation risks. In parallel, there has been a growing and very significant trend to develop a new generation of reactor simulation tools that rely more and more on first principles. It is safe to say that the next generation of innovative nuclear systems will be assessed with a completely new set of tools, more science based, in sharp contrast with what has been done in the past. However, the studies mentioned above point out that the present uncertainties in nuclear data should be significantly reduced in order to fully benefit from advances in modeling and simulation. Only a parallel effort in advanced simulation and nuclear data improvement will be able to provide designers with more general and well validated calculational tools to meet new design target accuracies. One further consideration related to the development of new advanced simulation tools is that there should be a more explicit link with the more fundamental physics parameters underlying the models used to describe cross sections that would avoid the use of processed, application-oriented, data (like multigroup cross sections). Finally, current methodologies for reducing uncertainties coming from nuclear data, which rely on the use of integral experiment information to perform statistical multigroup (i.e., energy spectrum weighted) cross section data assimilation should evolve to embrace new frontiers in advanced simulation. One of the drawbacks of the classical methodologies is related to the energy group structure and the type of neutron energy spectrum that are adopted in the assimilation (adjustment). In fact, after such an adjustment is performed, neutronic designers are then tied to this energy group structure and neutron energy spectrum when carrying out further calculations. In reality, this can be quite a limiting factor in view of the complex spectral issues that are involved in most reactor physics. This work combines novel, but proven, methodologies for overcoming these limitations. In fact, this is the first attempt to build up a link between the wealth of precise integral experiments and a basic theory of nuclear reactions. Essential ingredients of such a procedure, denominated here as assimilation, are covariances for model parameters and sensitivity matrices. The latter provide direct link between reaction theory and integral experiments. The result is a consistent data assimilation performed directly on the basic nuclear physics parameters that are being used in a variety of nuclear reaction mechanisms. The resulting improvement in their performance will consequently reduce related uncertainties when employed in reactor calculations. By using integral reactor physics experiments (meter scale), information is propagated back to the nuclear physics level (femtometers) covering a range of more than 13 orders of magnitude. The assimilation procedure should result in more accurate and more reliable evaluated data files of universal validity rather than tailored to a particular application. In fact, after data assimilation is carried out, the basic nuclear data file can be processed by a dedicated code into any energy group structure that the reactor physicist deems to be useful. On the other hand, integral experiments used in the assimilation should provide additional, possibly quite strict, constraints on the parameters entering nuclear reaction modeling, as well as the reaction models themselves. This report describes three years of combined research by Brookhaben National Lab (BNL) and Idaho National Lab (INL) on establishing viable assimilation methodology. The emphasis of this paper is on the empire code calculations to prepare the priors, sensitivity matrices and covariances for the model parameters. For completeness, we also include a short summary of the assimilation results produced by INL and reported earlier in annual reports [6], [7], [8].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2015

TU-CD-BRD-00: Incident Learning / RO-ILS

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-CD-BRD-01: Making Incident Learning Practical and Useful: Challenges and Previous Experiences

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-CD-BRD-02: Henry Ford Hospital System Experience, with Focus On Motivating and Reviewing

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-CD-BRD-03: UCSD Experience, with Focus On Implementing Change

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-CD-BRD-04: UCLA Experience, with Focus On Developing Metrics and Using RO-ILS

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

From noise to information: The transfer function formalism for uncertainty quantification in reconstructing the nuclear density

The neutron distribution of neutron-rich nuclei provides critical information on the structure of finite nuclei and neutron stars. Parity violating experiments—such as PREX and CREX—provide a clean and largely model-independent determination of neutron densities. Such experiments, however, are challenging and expensive, which is why sound statistical arguments are required to maximize the information gained. We introduce a new framework, the “transfer function formalism,” aimed at uncertainty quantification, model selection, and experimental design in the context of neutron densities. The transfer functions (TFs) are built analytically by expressing the linear response of the objective function (e.g., χ2) to small perturbations of the data. Using the TF formalism, we are able to analyze the expected overall uncertainty—quantified in terms of bias and variance—of the mean square radius and interior density of 48 Ca and 208 Pb. Using relativistic mean field models as a proxy for the weak-charge density—and assuming that a total of five measurements could be performed on the weak form factor of 48 Ca and 208 Pb—we identify the optimal models and experimental locations that minimize the uncertainty in the extraction of the radius and interior density. We also explore the use of the TF formalism to understand the influence of prior distributions for the model parameters, as well as the optimization of model hyperparameters not constrained by the data. Here,we establish how the choice of experimental locations and the model that is used can have a significant impact on the final uncertainties of the extracted quantities of interest. For challenging experiments such as CREX and PREX, a proper quantification of such uncertainties is critical. We have demonstrated how the TF formalism provides several advantages for this type of analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Estimating the joint distribution of rate parameters across multiple reactions in the absence of experimental data

Here, a procedure for determining the joint uncertainty of Arrhenius parameters across multiple combustion reactions of interest is demonstrated. This approach is capable of constructing the joint distribution of the Arrhenius parameters arising from the uncertain measurements performed in specific target experiments without having direct access to the underlying experimental data. The method involves constructing an ensemble of hypothetical data sets with summary statistics consistent with the available information reported by the experimentalists, followed by a fitting procedure that learns the structure of the joint parameter density across reactions using this consistent hypothetical data as evidence. The procedure is formalized in a Bayesian statistical framework, employing maximum-entropy and approximate Bayesian computation methods and utilizing efficient Markov chain Monte Carlo techniques to explore data and parameter spaces in a nested algorithm. We demonstrate the application of the method in the context of experiments designed to measure the rates of selected chain reactions in the H 2 -O 2 system and highlight the utility of this approach for revealing the critical correlations between the parameters within a single reaction and across reactions, as well as for maximizing consistency when utilizing rate parameter information in predictive combustion modeling of systems of interest.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2012

Q{sub weak} target performance

The Q{sub weak} Experiment at Jefferson Laboratory aims to measure the parity violating ep scattering asymmetry at low Q2 to a statistical precision of only 5 ppb. Such precision presents many challenges for the liquid-hydrogen target used in the experiment. The 35 cm long Q{sub weak} target was designed to withstand 180 #mu#A of beam current. Although this is the highest power cryotarget ever built, the target must also provide < 50 ppm of target noise under these demanding conditions, which makes it the lowest noise target ever built at the same time. These seemingly mutually exclusive goals have both been met. The target will be described, and measurements of its performance will be presented.

43 PARTICLE ACCELERATORS↗

DOE OSTI2014

Estudio de interacciones hadrónicas con $\Lambda^0\Lambda^0y \Lambda^0 p\pi^-$ en el estado final

Interactions between hadronic particles are studied. Data collected by the fixed target experiment SELEX at Fermilab, which took data in 1996-97, were used. It was a multi-stage spectrometer, with high forward acceptance (xf >0.1). It was designed for high statistic systematic studies of the production mechanisms of hadrons. It used a Σ− y π − beam of 600 GeV/c and a proton beam of 540 GeV/c, interacting with copper and carbon targets. We found an accumulation in the invariant mass of Λ0Λ 0 at 2340 MeV/c2 with a width of 14 MeV; and in Λ0pπ− a 2215 MeV/c2 accumulation with a width of 1.9 MeV. Those accumulations indicate the first observation of a new particle and its excited state.

Reyes Ramos, Rocío↗

DOE OSTI2012

Modernizing the Fission Basis (Experimental Progress Report)

In 2010 a proposal (Modernizing the Fission Basis) was prepared to 'resolve long standing differences between LANL and LLNL associated with the correct fission basis for analysis of nuclear test data'. Collaboration between LANL/LLNL/TUNL has been formed to implement this program by performing high precision measurements of neutron induced fission product yields as a function of incident neutron energy. This new program benefits from successful previous efforts utilizing mono-energetic neutrons undertaken by this collaboration. The first preliminary experiment in this new program was performed between July 24-31, 2011 at TUNL and had 2 main objectives: (1) demonstrating the capability to measure characteristic {gamma}-rays from specific fission products; (2) studying background effects from room scattered neutrons. In addition, a new dual fission ionization chamber has been designed and manufactured. The production design of the chamber is shown in the picture below. The first feasibility experiment to test this chamber is scheduled at the TUNL Tandem Laboratory from September 19-25, 2011. The dual fission chamber design will allow simultaneous exposure of absolute fission fragment emission rate detectors and the thick fission activation foils, positioned between the two chambers. This document formalizes the earlier experimental report demonstrating the experimental capability to make accurate (< 2 %) precision gamma-ray spectroscopic measurements of the excitation function of high fission product yields of the 239 Pu(n,f) reaction (induced by quasimonoenergetic neutrons). A second experiment (9/2011) introduced an compact double-sided fission chamber into the experimental arrangement, and so the relative number of incident neutrons striking the sample foil at each bombarding energy is limited only by statistics. (The number of incident neutrons often limits the experimental accuracy.) Fission chamber operation was so exceptional that 2 more chambers have been fabricated; thus fission foils of different isotopes may be left in place with sample changes. The scope of the measurements is both greatly expanded and the results become vetted. Experiment 2 is not reported here. A continuing experiment has been proposed for February 2012.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Predicting the performance uncertainty of a 1-MW pilot-scale carbon capture system after hierarchical laboratory-scale calibration and validation

A challenging problem in designing pilot-scale carbon capture systems is to predict, with uncertainty, the adsorber performance and capture efficiency under various operating conditions where no direct experimental data exist. Motivated by this challenge, we previously proposed a hierarchical framework in which relevant parameters of physical models were sequentially calibrated from different laboratory-scale carbon capture unit (C2U) experiments. Specifically, three models of increasing complexity were identified based on the fundamental physical and chemical processes of the sorbent-based carbon capture technology. Results from the corresponding laboratory experiments were used to statistically calibrate the physical model parameters while quantifying some of their inherent uncertainty. The parameter distributions obtained from laboratory-scale C2U calibration runs are used in this study to facilitate prediction at a larger scale where no corresponding experimental results are available. In this paper, we first describe the multiphase reactive flow model for a sorbent-based 1-MW carbon capture system then analyze results from an ensemble of simulations with the upscaled model. The simulation results are used to quantify uncertainty regarding the design’s predicted efficiency in carbon capture. In particular, we determine the minimum gas flow rate necessary to achieve 90% capture efficiency with 95% confidence.

bubbling bed↗

DOE OSTI2012

Fuel Cycle Research & Development: Technical Monthly – June 2012

Topics are: (1) MPACT Campaign - (a) Management and Integration • Coordination meetings between NE and NA-22, NA-24, and NA-82 were conducted the week of June 11th. Preparations are being made for the next MPACT working group meeting, scheduled for Aug 28-30 at Idaho Falls. In addition to covering accomplishments and discussing future plans, a site tour of INL facilities (MFC, EBR, ATR, INTEC) is being organized. (2) Accounting and Control Technologies - (a) Microcalorimetry • Now operating 256-pixel array at LANL. We are in the process of tuning detector parameters to improve and optimize performance. Preliminary measurements show approximate number of live pixels is similar to that observed previously at NIST. Continuing to study contribution to systematic error from uncertainties in tabulated gamma-ray energies. (b) Electrochemical Sensor • Testing of sensors fashioned from different precursor materials continued. SEM analysis of all used sensors has been or will be performed. (c) Lead Slowing Down Spectrometer • Ongoing perturbation calculations are providing information on the fundamental systematic error limits of LSDS. In order to achieve separating the contribution of Pu and 235U to the signal, there will need to be tight controls on systematic errors. Continuing to look into a He4 detector. Research into local construction of a He4 detector continued. We have started to apply the algorithm to test the LSDS using experimental data from previous RPI measurements. PNNL also developed a plan to address the lack of statistics in the MCNP modeling of the NGSI 64 assemblies. The ISU graduate student built and tested a fission chamber to gain experience with them. (d) Fast Neutron Imaging to Quantify Nuclear Materials • The imaging detector design was modified for each pixel to have an 8 x 8 pixel array. Quotations and purchasing process for components, including the new PSD scintillator are in progress. (e) Fast Neutron Multiplicity Analysis • The team submitted two papers to the upcoming INMM meeting that are related to the fast neutron multiplicity R&D effort. Progress was made on the project's main goal of designing a concept for a prototype fast-neutron multiplicity counter. We started laying out the outline for the final report. We have been working with our ORNL collaborators to develop a new digitizer system to support our experimental campaign planned for next year. (3) MPACT Analysis Tools - (a) Multi-isotope Process Monitor • Fuel characterization framework development continued during June. A report describing the methodologies is being completed. Kenneth Dayman, from University of Texas, spent a week at PNNL wrapping up his master's research and working on a journal submission covering that work. The target journal is the IEEE transactions on Nuclear Science; submission is planned for the end of July. A proposal to instrument H-Canyon is being prepared in conjunction with SRNL and the NNSA's NGSI program. The impact of gamma-ray spectrum counting statistics on the precision of relative radioisotope component intensities as reconstructed via Principal Component Regression (PCR) continued in June with Monte Carlo simulations of a two-component (i.e., two radioisotope) system. This work generalizes earlier studies in FY12 in which Poisson counting variations of only a single spectrum component were simulated. (b) Modeling and Simulation for Analysis of Safeguards Performance (Electrochemical) • Preliminary insights into safeguards challenges and the initial design for an electrochemical plant have been written up into an INMM paper and will be presented at the INMM Summer Meeting. Work is currently adding a new visualization capability for integrating materials accountancy with physical protection. (c) Material Control including Process Monitoring (Pattern Recognition, Sensors) • Fabrication of quartz chips continued at an external foundry. Awaiting delivery of the heat exchange manifold and chip holder. (d) MPACT System Integration and Technical Support • The initial report on cost-basis metrics for nuclear material security risk and proliferation risk was completed as scheduled. (4) Safeguards and Security by Design - (a) Used fuels storage security analysis, guidance and best practices • RFP was finalized and sent out. Awaiting response from World Institute for Nuclear Security. Coordinated with Scott Demuth on joint report • LANL milestone on best practices. Attended Nuclear Energy Institute National Nuclear Security Conference. Developed plan for soliciting input on prioritized issues for used fuel storage security. Worked on setting up a meeting with the Nuclear Regulatory Commission. Worked on FY2013 work package planning.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

Mechanical Model of Globular Transition in Polymers

In complex, multicomponent systems, polymers often undergo phase transitions between distinct conformations. This paper reports a millimeter-scale granular model of coil-to-globule transitions: one “polymer” chain—a cylinders-on-a-string “pearl necklace”—and many spheres, all shaken on a horizontal surface. It is possible to describe the behavior of this granular system by using formalisms generally used in statistical physics of polymers. Two sets of experiments allowed the observation of first- and second- order coil-to-globule transitions. The model shows that the competition between long- and short range interactions leads to a first-order transition. Well-designed granular system represents another kind of approach to the study of polymer phase transitions and might inspire future designs of polymer-like mesoscale systems.

36 MATERIALS SCIENCE↗

DOE OSTI2012

Application of 'Six Sigma{sup TM}' and 'Design of Experiment' for Cementation - Recipe Development for Evaporator Concentrate for NPP Ling AO, Phase II (China) - 12555

Cementation of radioactive waste is a common technology. The waste is mixed with cement and water and forms a stable, solid block. The physical properties like compression strength or low leach ability depends strongly on the cement recipe. Due to the fact that this waste cement mixture has to fulfill special requirements, a recipe development is necessary. The Six Sigma{sup TM}' DMAIC methodology, together with the Design of experiment (DoE) approach, was employed to optimize the process of a recipe development for cementation at the Ling Ao nuclear power plant (NPP) in China. The DMAIC offers a structured, systematical and traceable process to derive test parameters. The DoE test plans and statistical analysis is efficient regarding the amount of test runs and the benefit gain by getting a transfer function. A transfer function enables simulation which is useful to optimize the later process and being responsive to changes. The DoE method was successfully applied for developing a cementation recipe for both evaporator concentrate and resin waste in the plant. The key input parameters were determined, evaluated and the control of these parameters were included into the design. The applied Six Sigma{sup TM} tools can help to organize the thinking during the engineering process. Data are organized and clearly presented. Various variables can be limited to the most important ones. The Six Sigma{sup TM} tools help to make the thinking and decision process trace able. The tools can help to make data driven decisions (e.g. C and E Matrix). But the tools are not the only golden way. Results from scoring tools like the C and E Matrix need close review before using them. The DoE is an effective tool for generating test plans. DoE can be used with a small number of tests runs, but gives a valuable result from an engineering perspective in terms of a transfer function. The DoE prediction results, however, are only valid in the tested area. So a careful selection of input parameter and their limits for setting up a DoE is very important. An extrapolation of results is not recommended because the results are not reliable out of the tested area. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Perspectives on Polyolefin Catalysis in Microfluidics for High-Throughput Screening: A Minireview

Polyolefins are the largest produced plastics in the world which traditionally employ continuous stirred tank reactors and fluidized bed reactors for commercial production. The operating condition, reaction kinetics, and molecular interactions inside the reactor strongly affect the polyolefin properties, which require stringent process control in conventional procedures. Understanding the catalytic pathway, behavior of polymer particles and effect of reactor conditions are essential for designing specific polymer properties, namely the molecular weight, chain length, polydispersity, etc. Microfluidics can play a significant role in designing polymers tailored to the user needs. Smaller channel dimensions help obtain uniform reaction conditions over the length of the microfluidic reactor in a controlled environment. With real-time monitoring techniques in microfluidics, even single particle growth of polymer can be studied to understand the parameters affecting the polymer properties. High throughput microfluidics can help catalyst screening in a short duration with less consumption of reagents generating less waste. When supplemented with efficient machine learning algorithms, automated high throughput microfluidics has the potential to rapidly optimize the process and develop new knowledge even with a limited data set. When trained on data sets generated using microfluidic experiments that are designed efficiently with working knowledge of the process, machine learning algorithms can provide the relationship between the multivariable parameters space and polymer properties, which is not possible with the traditional statistical methods and interpolation techniques. Here, the rise in the utilization of microfluidics, with the advancement of machine learning algorithms, for polyolefin catalysis, highlights the importance of microfluidics for catalyst discovery, parameter optimization, and understanding reaction pathway for producing polymers with specific properties for specialized applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Responsiveness of miscanthus and switchgrass yields to stand age and nitrogen fertilization: A meta‐regression analysis

Abstract Optimal management of the perennial bioenergy crops, miscanthus and switchgrass, requires an understanding of their responsiveness to nitrogen (N) fertilizer at different maturity stages across locations and growing conditions. Earlier studies that have examined the yield response of these crops to N and stand age using field experiments or meta‐analysis techniques provide mixed evidence. We extend earlier studies by applying a multi‐level mixed‐effects (MLME) meta‐regression model to conduct a more extensive multivariate regression of yield response of these crops to N and stand age, while controlling for climate and location conditions and unobserved factors related to study design. Our findings are based on 1403 and 2811 yield observations for miscanthus and switchgrass, respectively, from experiments conducted between 2002 and 2019 across the rainfed region in the United States. We find statistically significant evidence that an additional year of maturity increases miscanthus and switchgrass yields but at a decreasing rate; yields peak at the 7th and 6th year respectively, for the observed range of applied N rates and stands. We also find that an increase in N application increases yield by a statistically significant level, but at a declining rate; the magnitude of the yield response to N is, however, small and varies with the age of the crop. The impact of N is larger on older compared to younger and middle‐aged stands of miscanthus. In contrast, the impact of N on switchgrass is larger on middle‐aged compared to younger and older stands of switchgrass. We do not find a statistically significant effect of soil productivity on yield for either crop. This analysis provides a basis for developing N application recommendations and optimal rotation age for miscanthus and switchgrass and shows that these energy crops can grow just as productively on low productivity land as on high productivity land.

59 BASIC BIOLOGICAL SCIENCES↗