Predictive models of carbon capture systems and their validation using bench scale and pilot scale data

Predictive steady-state and dynamic models are essential for optimal design and scale up of CO2 capture processes. The models should be able to predict accurately across all scales and required operating conditions with quantified uncertainty. The U.S. Department of Energy’s Carbon Capture Simulation Initiative (CCSI) process modeling team has been working on the development of a framework to develop such models. This framework is demonstrated on a typical amine-based system which is highly non-ideal and can exhibit large nonlinearities and therefore serves as a nice platform to test the framework. To validate both steady state and dynamic models developed using this framework, the team recently collaborated with the National Carbon Capture Center (NCCC) in Wilsonville, AL to obtain both steady-state and dynamic data under widely varying operating conditions. The dynamic test runs were conducted by introducing step changes in the solvent, flue gas, and reboiler steam flowrates and recording the transients of all key variables. The step tests were designed to approximately maintain persistence of excitation in order to provide information across the entire spectrum of data including both high and low frequency information. The measured data include the transient response of all the sensors in the pilot plant including the gas composition sensors. Due to measurement noise and inconsistencies in the sensor data, a dynamic data reconciliation approach is developed to guarantee mass and energy balances. This framework for the development of predictive models is then extended to a non-aqueous solvent that is under development. This solvent can be regenerated at a much higher pressure than the traditional amine solvents and therefore can result in reduced energy penalty for desorption as well as reduction in energy requirement for CO2 compression. However this solvent has much higher viscosity compared to traditional solvents and exhibits significantly different thermodynamic and transport properties resulting in numerous modeling challenges. The steady-state model of this high-viscosity solvent is validated by using the bench scale data

FMEA of MR-Only Treatment Planning in the Pelvis

Purpose: To evaluate the implementation of a magnetic resonance (MR)-only workflow (ie, implementing MR simulation as the primary planning modality) using failure mode and effects analysis (FMEA) in comparison with a conventional multimodality (MR simulation in conjunction with computed tomography simulation) workflow for pelvis external beam planning. Methods and Materials: To perform the FMEA, a multidisciplinary 9-member team was assembled and developed process maps, identified potential failure modes (FMs), and assigned numerical values to the severity (S), frequency of occurrence (O), and detectability (D) of those FMs. Risk priority numbers (RPNs) were calculated via the product of S, O, and D as a metric for evaluating relative patient risk. An alternative 3-digit composite number (SOD) was computed to emphasize high-severity FMs. Fault tree analysis identified the causality chain leading to the highest-severity FM. Results: Seven processes were identified, 3 of which were shared between workflows. Image fusion and target delineation subprocesses using the conventional workflow added 9 and 10 FMs, respectively, with 6 RPNs \u3e100. By contrast, synthetic computed tomography generation introduced 3 major subprocesses and propagated 46 unique FMs, 15 with RPNs \u3e100. For the conventional workflow, the largest RPN scores were introduced by image fusion (RPN range, 120-192). For the MR-only workflow, the highest RPN scores were from inaccuracies in target delineation resulting from misinterpretation of MR images (RPN = 240) and insufficient management of patient- and system-level distortions (RPN = 210 and 168, respectively). Underestimation (RPN = 140) or overestimation (RPN = 192) of bone volume produced higher RPN scores. The highest SODs for both workflows were related to changes in target location because of internal anatomy changes (conventional = 961, MR-only = 822). Conclusions: FMEA identified areas for mitigating risk in MR-only pelvis RTP, and SODs identified high-severity process modes. Efforts to develop a quality management program to mitigate high FMs are underway

Long‐lived Snell dwarf mice display increased proteostatic mechanisms that are not dependent on decreased mTORC1 activity

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111144/1/acel12329.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/111144/2/acel12329-sup-0001-SuppInfo.pd

The American Association for the Surgery of Trauma renal injury grading scale: Implications of the 2018 revisions for injury reclassification and predicting bleeding interventions.

BackgroundIn 2018, the American Association for the Surgery of Trauma (AAST) published revisions to the renal injury grading system to reflect the increased reliance on computed tomography scans and non-operative management of high-grade renal trauma (HGRT). We aimed to evaluate how these revisions will change the grading of HGRT and if it outperforms the original 1989 grading in predicting bleeding control interventions.MethodsData on HGRT were collected from 14 Level-1 trauma centers from 2014 to 2017. Patients with initial computed tomography scans were included. Two radiologists reviewed the scans to regrade the injuries according to the 1989 and 2018 AAST grading systems. Descriptive statistics were used to assess grade reclassifications. Mixed-effect multivariable logistic regression was used to measure the predictive ability of each grading system. The areas under the curves were compared.ResultsOf the 322 injuries included, 27.0% were upgraded, 3.4% were downgraded, and 69.5% remained unchanged. Of the injuries graded as III or lower using the 1989 AAST, 33.5% were upgraded to grade IV using the 2018 AAST. Of the grade V injuries, 58.8% were downgraded using the 2018 AAST. There was no statistically significant difference in the overall areas under the curves between the 2018 and 1989 AAST grading system for predicting bleeding interventions (0.72 vs. 0.68, p = 0.34).ConclusionAbout one third of the injuries previously classified as grade III will be upgraded to grade IV using the 2018 AAST, which adds to the heterogeneity of grade IV injuries. Although the 2018 AAST grading provides more anatomic details on injury patterns and includes important radiologic findings, it did not outperform the 1989 AAST grading in predicting bleeding interventions.Level of evidencePrognostic and Epidemiological Study, level III

State of the Art: Small Spacecraft Technology

This report provides an overview of the current state-of-the-art of small spacecraft technology, with particular emphasis placed on the state-of-the-art of CubeSat-related technology. It was first commissioned by NASAs Small Spacecraft Technology Program (SSTP) in mid-2013 in response to the rapid growth in interest in using small spacecraft for many types of missions in Earth orbit and beyond, and was revised in mid-2015 and 2018. This work was funded by the Space Technology Mission Directorate (STMD). For the sake of this assessment, small spacecraft are defined to be spacecraft with a mass less than 180 kg. This report provides a summary of the state-of-the-art for each of the following small spacecraft technology domains: Complete Spacecraft, Power, Propulsion, Guidance Navigation and Control, Structures, Materials and Mechanisms, Thermal Control, Command and Data Handling, Communications, Integration, Launch and Deployment, Ground Data Systems and Operations, and Passive Deorbit Devices