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At least 307 records · Page 17

Nonlinear multiobjective and dynamic real-time predictive optimization for optimal operation of baseload power plants under variable renewable energy

Considering the increase of disruptive variable renewable energy penetration into the power grid, this article focuses on the investigation of a multiobjective and dynamic real-time optimization framework to address the cycling of large-scale power plants under renewable penetration. In this framework, a parallelized particle swarm optimization step is first performed to generate feasible initial points. Then, a multiobjective and dynamic real-time optimization formulation generates optimal trajectories. Further, the benefit of predictive capability is investigated for the dynamic component, which introduces the novel nonlinear multiobjective and dynamic real-time predictive optimization approach. Two multiobjective formulations to obtain Pareto front optimal in real time are explored: the modified Tchebycheff-based weighted metric and ϵ-constraint methods. Economic and environmental objectives are considered in this study. A novel topical discussion on the intersection of dynamic real-time optimization with model predictive control is also presented. The developed framework is successfully applied to a baseload coal-fired power plant with postcombustion CO 2 capture. Results indicate that the approach can be deployed for a large-scale system if automatic differentiation, model reduction, and parallelization are adopted to improve computational tractability, with computational improvement up to 120-folds after performing these steps. Finally, market and carbon policies showed an impact on the optimal compromise between the objectives with an additional 63 ton of CO 2 captured under favorable market conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Attribution of heterogeneous stress distributions in low-grain polycrystals under conditions leading to damage

In high-purity polycrystalline metallic materials, voids tend to favor grain boundaries as nucleation sites due to the elevated stress states produced by granular interactions and the weakened grain boundary from the relative atomic disorder. To quantify the key factors of this elevated stress state, simple compression of a small multi-grain cylinder of body-centered cubic tantalum was simulated using a single crystal plasticity model that incorporates non-Schmid effects. Four increasingly complex synthetic microstructures were created to tractably incorporate grain boundary interactions, and a statistically significant number of combinations were performed by varying the initial crystallographic orientations of the microstructure. Most of these simulations produce the maximum von Mises stress on a grain boundary and less frequently at the multi-grain junctions. To build a statistical model for the maximum von Mises stress at the grain boundary, physically based features that could contribute to the elevated stress state were selected. Then, a learning algorithm based on information theory was used to identify which of these features contributed the most information to the data set. The identified features include a grain’s propensity to accommodate both elastic and plastic deformations and their directional components. The misalignment of the direction of each grain’s mechanical response was found to be strongly correlated to the magnitude of the stress near the grain boundary. For all of the synthetic microstructures, the statistical models produce a residual distribution that is nearly Gaussian with a variance of, at most, 10% of the prior distribution. The successful performance of the statistical model implies the correct identification of the physical features that cause severe stress localization in polycrystalline materials. The statistical models constructed here can be used to formulate a physically motivated void nucleation model which is sensitive to a microstructure’s propensity to produce elevated stress states. As a result, these statistical models also enable the design of material microstructures, in which the crystallographic orientation is chosen to resist void nucleation.

36 MATERIALS SCIENCE↗

Plutonium-238 Loadout Calorimeter Return To Service

The calorimeter in the transfer area in Building 7920 at the US Department of Energy’s Oak Ridge National Laboratory is used to measure the amount of 238 Pu in the Plutonium Heat Source Oxide. The calorimetry measurement is taken after the oxide is packaged in an ORISC (Oak Ridge Inner Shipping Capsule)/FSO (Fuel Storage Outer) assembly before loading into the Containment Vessel and shipping container. The equipment is used in three specific configurations: zero measurement (nothing in the sample cup), FSO measurement (actual measurement of 238 Pu), and reference calibration measurement (using the reference FSO as a known heat source). System checks were performed in July 2023 in preparation for scheduled material loadout. During these checks, personnel discovered that the reference FSO had experienced an electrical short in the heater cable and was no longer functional. The calorimeter was in the reference calibration measurement configuration at this time. Facility management was notified when the damage was discovered. The data from the Yokogawa recorder were pulled and analyzed for a span of time between September 2022 and July 2023. An unusual spike was found in the sample cup temperature data that started on October 19, 2022, and ended on October 20, 2022. The sample cup reached a temperature of 191.1°C. The maximum allowable temperature for the calorimeter thermopile to reach is 220°C based on the manufacturer statement provided in Appendix B of this report [1]. The calorimeter thermopile and the sample cup thermocouple are physically close to each other; therefore, the data suggest that the calorimeter itself never saw a temperature in excess of 191.1°C. Physical damage present on the cable, tape, and insulation suggests that the temperature reached a higher value in some locations within the sample cup than the data shows. Because of this discrepancy, testing of the calorimeter was required to confirm that the calorimeter is functioning the same as it was before the electrical short. The intent of this report is to assess the functionality of the calorimeter and determine if it is acceptable to use for 238 Pu loadout material measurement. Testing showed that the calorimeter is functionally equivalent to the initial calibration that was performed in the summer of 2021, and thus, the calorimeter was cleared to be used for its intended purposes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Constructing uniform oxygen defect engineering on primary particle level for high-stability lithium-rich cathode materials

Lithium-rich layered cathode materials are considered to be research focus of cathode candidates for next generation lithium-ion batteries due to their high specific capacity and low cost. However, lattice deoxidation associated with elemental migration and internal local shrinkage usually results in deteriorated cyclic performance and notorious voltage attenuation, severely limiting its application. In this paper, we have successfully injected uniform oxygen defects into surface region of Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2 primary particles under the high-pressure and weak carbonate environment. Various experimental investigations indicate that the injected robust oxygen defects can not only mitigate detrimental interfacial reactions but also suppress unfavorable lattice variation and particle breakage. More importantly, theoretical calculations unravel the critical roles of oxygen defects in regulating energy band structure for strengthened anionic reversibility. Owing to stabilization effects of unique oxygen defect engineering, the modified Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2 cathode has harvested dramatically enhanced electrochemical performance including a high initial coulombic efficiency of 96.6%, an outstanding capacity retention of 91.96% (1C, 200 cycles) and suppressed voltage decay of only 1.62 mV per cycle. Therefore, this facile and effective defect engineering strategy could establish new guidance for promoting practical application of Li-rich Mn-based cathode material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A new mechanism of stabilizing SEI of Si anode driven by crosstalk behavior and its potential for developing high performance Si-based batteries

Stabilizing solid electrolyte interphase (SEI) is a key factor for determining cell performance of Silicon (Si) anode, such as safety, cycle lifetime, and calendar lifetime. Here, we found a new potential for stabilizing SEI of the Si anode, driven by crosstalk with cathode material. Here we investigated the effect of crosstalk on the chemistry of SEI of the Si anode as a function of three different, representative cathode materials: LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC532), LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811), and LiFePO 4 (LFP). Specifically, we observed that crosstalk significantly affected the formation and growth mechanism of SEI layer on the Si anodes. Unexpectedly, dissolved Fe ions from the LFP cathode has a positive impact on the chemistry and electrochemical stability of the SEI layer of Si anode compared to the other cathodes, resulting in better electrochemical performance in terms of initial coulombic efficiency and capacity fade.

25 ENERGY STORAGE↗

Tensile properties of co-rolled Zr/U-10Mo fuel at ambient and elevated temperatures

The United States High Performance Research Reactor (USHPRR) initiative is currently interested in replacing high-enriched uranium fuel in research reactors with high-assay low-enriched uranium fuel. Here, this work aimed to assist in that mission by providing tensile and bend test data on bare U-Mo and tensile test data on co-rolled Zr/U-10Mo plates at differing thicknesses (0.285 mm, 0.300 mm, and 0.465 mm) and temperatures (293 K, 473 K, and 623 K). Yield strength and ultimate tensile strength values are reported along with an in-depth comparison of how temperature, rolling direction, thickness, and the presence of the Zr-interlayer affect mechanical properties. Results showed that yield strength and ultimate tensile strength in Zr/U-10Mo foils lower as temperature increases by approximately 300 MPa from 293 to 473 K, and another 100 MPa from 473 to 623 K. Additionally it was found that with increased temperature, there is less differentiation in fuel necking and delamination behavior, as well as a greater perceived elongation to fracture. The elastic modulus of co-rolled mini-plates does not follow the volumetric rule of mixtures in terms of averaged strength and is actually lower than the reported moduli of both Zr and U-10Mo.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Adaptive learning-driven high-throughput synthesis of oxygen reduction reaction Fe–N–C electrocatalysts

Reducing human reliance on inefficient energy systems and fossil fuels has become more urgent due to the consequences of global climate change. However, traditional trial-and-error approaches have hampered our ability to accelerate the discovery and implementation of functional materials for efficient energy conversion devices, such as polymer electrolyte fuel cells (PEFCs). To address this, we develop an adaptive learning framework that integrates machine learning and state-of-the-art capabilities in high-throughput synthesis to achieve expedited optimization of iron-nitrogen-carbon PEFC oxygen reduction reaction (ORR) electrocatalysts. We use statistical inference, uncertainty quantification, and global optimization to build a computational design-of-experiment tool that identifies the optimum compositions to be investigated next to reduce the demands placed on experimental materials discovery. We benchmark the ability of the proposed strategy to discover optimum catalyst synthesis conditions in a six-dimensional search space when starting with a thirty-six-sample database. By following the adaptive learning strategy, we synthesize fourteen new catalysts from approximately ten billion unique compositions and discover four catalysts that outperform all original samples. The best machine learning-optimized catalyst is 33% more active than the highest-performing one in the initial database, showing an ORR activity seven times larger than those typically reported for the same class of materials.

36 MATERIALS SCIENCE↗

An improved specimen preparation method for marine shallow gas-bearing sand sediments and its validations

Instabilities of shallow gas-charged seabed are potential geological hazards in ocean engineering. In practice, the conventional field sampling techniques failed to obtain undisturbed gas-bearing sediments from the seabed for laboratory mechanical testing because of sensitive gas exsolution and escape from sediments. However, preparation of representative remoulded gas-charged specimens is a challenging issue, because it is rather difficult to quantitatively control the gas content and obtain uniform distribution of gas bubbles within the specimen. Given the above problems, this work proposes a reliable approach to reconstitute the high-saturation specimen of gas-charged sediments in the laboratory by an improved multifunction integrated triaxial apparatus (MITA). This apparatus is developed based on an advanced stress path triaxial system by introducing a temperature-controlled system and a wave-monitoring system. The temperature-controlled system is used to accurately mimic the in situ environments of sediments in the seabed. The wave-monitoring system is utilized to identify exsolution point of free gas and examine the disturbance of gas to specimens during gas exsolution. The detailed procedure of gassy specimen preparation is introduced. Then, the quality of prepared specimens using our improved apparatus is validated by the high-resolution micro-X-ray computed tomography (μCT) scanning test, from which bubble occurrence and size distribution within the gassy sand specimen can be obtained; and preliminary mechanical tests on gassy sand specimens with various initial saturation degrees are performed. The proposed specimen preparation procedure succeeds in proving the postulated occurrence state of gas bubbles in coarse-grained sediments and accurately controlling the gas content.

58 GEOSCIENCES↗

Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations

Predictive modeling typically relies on Bayesian model calibration to provide uncertainty quantification. Variational inference utilizing fully independent (“mean-field”) Gaussian distributions are often used as approximate probability density functions. This simplification is attractive since the number of variational parameters grows only linearly with the number of unknown model parameters. However, the resulting diagonal covariance structure and unimodal behavior can be too restrictive to provide useful approximations of intractable Bayesian posteriors that exhibit highly non-Gaussian behavior, including multimodality. High-fidelity surrogate posteriors for these problems can be obtained by considering the family of Gaussian mixtures. Gaussian mixtures are capable of capturing multiple modes and approximating any distribution to an arbitrary degree of accuracy, while maintaining some analytical tractability. Unfortunately, variational inference using Gaussian mixtures with full-covariance structures suffers from a quadratic growth in variational parameters with the number of model parameters. The existence of multiple local minima due to strong nonconvex trends in the loss functions often associated with variational inference present additional complications, These challenges motivate the need for robust initialization procedures to improve the performance and computational scalability of variational inference with mixture models. In this work, we propose a method for constructing an initial Gaussian mixture model approximation that can be used to warm-start the iterative solvers for variational inference. The procedure begins with a global optimization stage in model parameter space. In this step, local gradient-based optimization, globalized through multistart, is used to determine a set of local maxima, which we take to approximate the mixture component centers. Around each mode, a local Gaussian approximation is constructed via the Laplace approximation. Finally, the mixture weights are determined through constrained least squares regression. The robustness and scalability of the proposed methodology is demonstrated through application to an ensemble of synthetic tests using high-dimensional, multimodal probability density functions. Here, the practical aspects of the approach are demonstrated with inversion problems in structural dynamics.

97 MATHEMATICS AND COMPUTING↗

Engineering the Microstructure and Morphology of Explosive Films via Control of Interfacial Energy

Physical vapor deposition of organic explosives enables growth of polycrystalline films with a unique microstructure and morphology compared to the bulk material. This study demonstrates the ability to control crystal orientation and porosity in pentaerythritol tetranitrate films by varying the interfacial energy between the substrate and the vapor-deposited explosive. Additionally, variation in density, porosity, surface roughness, and optical properties is achieved in the explosive film, with significant implications for initiation sensitivity and detonation performance of the explosive material. Various surface science techniques, including angle-resolved X-ray photoelectron spectroscopy and multiliquid contact angle analysis, are utilized to characterize interfacial characteristics between the substrate and explosive film. Optical microscopy and scanning electron microscopy of pentaerythritol tetranitrate surfaces and fracture cross sections illustrate the difference in morphology evolution and the microstructure achieved through surface energy modification. X-ray diffraction studies with the Tilt-A-Whirl three-dimensional pole figure rendering and texture analysis software suite reveal that high surface energy substrates result in a preferred (110) out-of-plane orientation of pentaerythritol tetranitrate crystallites and denser films. Low surface energy substrates create more randomly textured pentaerythritol tetranitrate and lead to nanoscale porosity and lower density films. This work furthers the scientific basis for interfacial engineering of polycrystalline organic explosive films through control of surface energy, enabling future study of dynamic and reactive detonative phenomena at the microscale. Results of this study also have potential applications to active pharmaceutical ingredients, stimuli-responsive polymer films, organic thin film transistors, and other areas.

36 MATERIALS SCIENCE↗

Ethanol Upgrading to n -Butanol Using Transition-Metal-Incorporated Poly(triazine)imide Frameworks

The upgrading of ethanol to n-butanol was performed using a molecular catalyst integrated into a carbon nitride support, one of the first examples of a supported molecular catalyst performing the Guerbet process. Initial studies using crystalline poly(triazine)imide (PTI) with lithium or transition-metal cations imbedded in the support together with a base as the catalyst system did not produce any significant amounts of n-butanol. However, when using the catalyst material formed by treatment of PTI-LiCl with [(Cp*)IrCl 2 ] 2 (Cp* = pentamethylcyclopentadienyl) along with sodium hydroxide, a 59% selectivity for butanol (13% yield) was obtained at 145 °C. This PTI-(Cp*)Ir material exhibited distinct UV–vis absorption features and powder X-ray diffractions which differ from those of the parent PTI-LiCl and [(Cp*)IrCl 2 ] 2 . Here, the PTI-(Cp*)Ir material was found to have a metal loading of 27% iridium per empirical unit of the framework. Along with the formation of n-butanol from the Guerbet reaction, the presence of higher chain alcohols was also observed.

Guerbet↗

Influence of Annealing Temperature on the OER Activity of NiO(111) Nanosheets Prepared via Microwave and Solvothermal Synthesis Approaches

Earth-abundant transition metal oxides are promising alternatives to precious metal oxides as electrocatalysts for the oxygen evolution reaction (OER) and are intensively investigated for alkaline water electrolysis. OER electrocatalysis, like most other catalytic reactions, is surface-initiated, and the catalyst performance is fundamentally determined by the surface properties. Most transition metal oxide catalysts show OER activities that depend on the predominantly exposed crystal facets/surface structure. Therefore, the design of synthetic strategies to obtain the most active crystal facets is of significant research interest. In this work, rock salt NiO OER catalysts with (111) predominantly exposed facets were synthesized by a solvothermal (ST) method either heated under supercritical or microwave-assisted (MW) conditions. Particular emphasis was placed on the influence of the post annealing temperature on the structural configuration and OER activity to compare their catalytic performances. The as-prepared electrocatalysts are pure α-Ni hydroxides which were converted to rock salt NiO (111) nanosheets with hexagonal pores after heat treatment at different temperatures. The OER activity of the electrodes has been evaluated in 0.1 M KOH using geometric and intrinsic current densities via normalization by the disk area and BET area, respectively. The lowest overpotential at a geometric current density of 10 mA/cm 2 is found for samples pretreated by heating between 400 and 500 °C with a catalyst loading of 115 μg/cm 2 . Despite the very similar nature of the catalysts obtained from the two methods, the ST electrodes show a higher geometric and intrinsic current density for 500 °C pretreatment. The MW electrodes, however, achieve an optimal geometric current density for 400 °C pretreatment, while their intrinsic current density requires pretreatment over 600 °C. Interestingly, pretreated electrodes show consistently higher OER activity as compared to the poorly crystalline/less ordered hydroxide as-prepared electrocatalysts. Thus, our study highlights the importance of the synthesis method and pretreatment at an optimal temperature.

36 MATERIALS SCIENCE↗

Controlled patterning of crystalline domains by frontal polymerization

Materials with hierarchical architectures that combine soft and hard material domains with coalesced interfaces possess superior properties compared with their homogeneous counterparts. These architectures in synthetic materials have been achieved through deterministic manufacturing strategies such as 3D printing, which require an a priori design and active intervention throughout the process to achieve architectures spanning multiple length scales. Here we harness frontal polymerization spin mode dynamics to autonomously fabricate patterned crystalline domains in poly(cyclooctadiene) with multiscale organization. This rapid, dissipative processing method leads to the formation of amorphous and semi-crystalline domains emerging from the internal interfaces generated between the solid polymer and the propagating cure front. The size, spacing and arrangement of the domains are controlled by the interplay between the reaction kinetics, thermochemistry and boundary conditions. Small perturbations in the fabrication conditions reproducibly lead to remarkable changes in the patterned microstructure and the resulting strength, elastic modulus and toughness of the polymer. Furthermore, this ability to control mechanical properties and performance solely through the initial conditions and the mode of front propagation represents a marked advancement in the design and manufacturing of advanced multiscale materials. Drawing inspiration from biological systems in which structural complexity develops through dissipative reaction–diffusion processes, this study explores a transformative synthetic manufacturing strategy aimed at harnessing the principles underpinning morphogenic growth, unlocking new avenues for advanced materials design and fabrication. Synthetic coupled reaction-transport processes offer a versatile yet relatively underexplored method to manipulate the spatial attributes of synthetic materials10. Here we introduce an innovative manufacturing approach based on frontal ring-opening metathesis polymerization (FROMP) that draws parallels with morphogenic growth and development, enabling the formation of patterned microstructures within polymeric materials.

36 MATERIALS SCIENCE↗

Federated Access from DOE Labs to Distributed Storage in the EIC Era of Computing

The Electron Ion Collider (EIC) collaboration and future experiment is a unique scientific ecosystem within Nuclear Physics as the experiment starts right off as a crosscollaboration between Brookhaven National Lab (BNL) & Jefferson Lab (JLab). As a result, this muti-lab computing model tries at best to provide services accessible from anywhere by anyone who is part of the collaboration. While the computing model for the EIC is not finalized, it is anticipated that the computational and storage resources will be made accessible to a wide range of collaborators across the world. The use of federated ID seems to be a critical element to the strategy of providing such services, allowing seamless access to each lab site computing resources. However, providing Federated access to a Federated storage is not a trivial matter and has its share of technical challenges. In this contribution, we focus on the steps we took towards the deployment of a distributed object storage system that integrates with Amazon S3 and Federated ID. We will first cover for and explain the first stage storage solutions provided to the EIC during the detector design phase. Our initial test deployment consisted of Lustre storage using MinIO, hence providing an S3 interface. High Availability load balancers were added later to provide the initial scalability it lacked. Performance of that system will be shown. While this embryonic solution worked well, it had many limitations. Looking ahead, the Ceph object storage is considered a top-of-the-line solution in the storage community - since the Ceph Object Gateway is compatible with the Amazon S3 API out of the box, our next phase will use a native S3 storage. Our Ceph deployment will consist of erasure coded storage nodes to maximize storage potential along with multiple Ceph Object Gateways for redundant access. We will compare performance of our next stage implementations. Finally, we will present how to leverage OpenID Connect with the Ceph Object Gateway’s to enable Federated ID access. We hope this contribution will serve the community needs as we move forward with cross-lab collaborations and the need for Federated ID access to distributed compute facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Design of a new charge exchange recombination spectroscopy diagnostic for impurity transport experiments at Wendelstein 7-X

In this study, we present the design of a new charge exchange recombination spectroscopy (CXRS) system for Wendelstein 7-X (W7-X), which aims at measuring line radiation from highly ionized iron impurities after laser blow off injections over transport timescales. New fiber bundles with a core diameter of 600 µm have been added to one of the existing optical systems at W7-X used for CXRS. The fibers direct collected light to five newly developed single channel high frame rate F/2.8 spectrometers. The new custom-made spectrometers are built using entirely off-the-shelf and 3D printed components, and employ a round-to-linear fiber bundle, instead of an entrance slit, to maximize light throughput. The detector is an ultra-low readout noise EM-CCD camera capable of frame rates of up to 10 000 fps for about 500 consecutive frames when operated using a single readout channel. Such high frame rates will enable the study of inward convection of injected impurities. An initial sensitivity study is performed using a newly developed Markov chain Monte Carlo approach based on the pySTRAHL impurity transport code. This study indicates that, with the addition of the new CX diagnostic, impurity convection velocities can be inferred.

Instruments & Instrumentation↗

Measuring nonlinearities of a cantilever beam using a low-cost efficient wireless intelligent sensor for strain (LEWIS-S)

In the context of experimental vibration data, strain gauges can obtain linear and nonlinear dynamic measurements. However, measuring strain can be disincentivizing and expensive due to the complexity of data acquisition systems, lack of portability, and high costs. This research introduces the use of a low-cost efficient wireless intelligent sensor for strain (LEWIS-S) that is based on a portable-sensor-design platform that streamlines strain sensing. Additionally, the softening behavior of a cantilever beam with geometric and inertial nonlinearities is characterized by the LEWIS-S based on high force level inputs. Two experiments were performed on a nonlinear cantilever beam with measurements obtained by the LEWIS-S sensor and an accelerometer. First, a sine sweep test was performed through the fundamental resonance of the system, then a ring-down test was performed from a large initial static deformation. Good agreement was revealed in quantities of interest such as frequency response functions, the continuous wavelet transforms, and softening behavior in the backbone curves.

42 ENGINEERING↗

Deep Neural Network Assisted Distributed Strain and Temperature Fiber Sensor System for Natural Gas Pipeline Monitoring

Natural gas pipeline integrity monitoring is crucial to detect potential leaks, find structural issues, and prevent environmental damage. This article presents a system of natural gas pipeline monitoring that uses a specialized double Brillouin peak sensing fiber along with the Brillouin optical time domain analysis (BOTDAs) technique. The calibrated sensing fiber coefficients for strain and temperature are 41.8 kHz/ με and 0.9 MHz/°C for peak 1; and 47.2 kHz/ με , and 1.11 MHz/°C for peak 2, respectively. Initially, lab tests were performed by installing a short section of double Brillouin peak fiber (DBPF) on a 1-in steel pipe under pressure up to 1000 per square inch (psi) at elevated temperatures. Simultaneous distributed measurements of temperature and pressure-induced hoop strain were successfully measured. Considering the long processing speed to extract Brillouin frequency shift (BFS), we employ a novel probabilistic deep neural network (PDNN) framework for rapid BFS prediction. Additionally, using the Finite Element Method, the effects of the pipeline pressure on hoop strain were modeled and compared to the experimental hoop strain under the same set of pipeline conditions. Finally, an actual 4-in outer diameter steel natural gas pipeline was used for pilot-scale tests, where hoop strain was measured at various pressure levels. Leaks were simulated to demonstrate accurate pipeline integrity monitoring. At an internal pipe pressure of 1000 psi, hoop strain of approximately 300 με was observed, and the sensitivity was calculated as 0.28 με /psi. The results of this pilot-scale study demonstrated that the system is capable of performing distributed monitoring sufficient to detect pipeline pressure and the presence of leaks to ensure the safe operation of gas pipelines in the field.

03 NATURAL GAS↗

Assessment of Low-Level Pu Isotope Ratio Measurements Using Multicollector Inductively Coupled Plasma Mass Spectrometry (MC-ICP-MS/MS) Equipped with a Pre-Mass Filter

We present an initial investigation into the performance of a multicollector inductively coupled plasmamass spectrometer equipped with a pre-mass filter (Neoma MC-ICP-MS/MS) for making plutonium (Pu) isotope ratio measurements on solutions containing low level (i.e., pg mL –1 ) Pu concentrations. This assessment was achieved by comparison of the 240 Pu/ 239 Pu, 241 Pu/ 239 Pu, and 242 Pu/ 239 Pu ratios attained over a one month period on the MC-ICP-MS/MS with the long-term (∼1 year) performance observed on the predecessor MC-ICP-MS (Neptune Plus) instrument each equipped with an equipped with an APEXΩ desolvating nebulizer for repeated measurements of certified reference materials from New Brunswick Program Office (NBL PO) CRM 136a and CRM 137. The MC-ICP-MS/MS performance of repeated measurement of CRM 136a (n = 20) resulted in mean values of 240 Pu/ 239 Pu = 0.1448 ± 0.0006, 241 Pu/ 239 Pu = 0.00371 ± 0.00006, and 242 Pu/ 239 Pu = 0.00682 ± 0.00006 (k = 2). The CRM 137 (n = 20), analyzed during the same analytical sessions, produced mean values for 240 Pu/ 239 Pu = 0.2414 ± 0.0006, 241 Pu/ 239 Pu = 0.00464 ± 0.00007, and 242 Pu/ 239 Pu = 0.0157 ± 0.0001 (k = 2). These results closely align with the certificate values for CRM 136a and CRM 137 and are within the k = 2 envelopes defined by the long-term performance of the traditional MC-ICP-MS approach (Neptune Plus). Examination of the performance of the various Pu isotope ratios as a function of total Pu content revealed accurate results (<3% relative difference, or RD) above ∼50 fg total Pu. The results presented here demonstrate the capability of the MC-ICP-MS/MS making accurate and precise low level Pu isotopic measurements. While the intent of this work was not to investigate the functionality of the collision cell, the pre-mass filter was employed. Future studies are warranted to investigate the entire capability of the MC-ICP-MS/MS collision cell and pre-cell mass filter optimization for performing low level Pu isotope measurements, even in mixed matrix samples.

CRM↗