Search NASA⌕ Search

SEARCH · Search NASA

Results for “systole”

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

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

Compensatory reserve detects subclinical shock with more expeditious prediction for need of life‐saving interventions compared to systolic blood pressure and blood lactate

Abstract Introduction We conducted a prospective observational study on 205 trauma patients at a level I trauma facility to test the hypothesis that a compensatory reserve measurement (CRM) would identify higher risk for progression to shock and/or need a life‐saving interventions (LSIs) earlier than systolic blood pressure (SBP) and blood lactate (LAC). Methods A composite outcome metric included blood transfusion, procedural LSI, and mortality. Discrete measures assessed as abnormal (ab) were SBP <90 mmHg, CRM <60%, and LAC >2.0. A graded categorization of shock was defined as: no shock (normal [n] SBP [n‐SBP], n‐CRM, n‐LAC); sub‐clinical shock (ab‐CRM, n‐SBP, n‐LAC); occult shock (n‐SBP, ab‐CRM, ab‐LAC); or overt shock (ab‐SBP, ab‐CRM, ab‐LAC). Results Three patients displayed overt shock, 53 displayed sub‐clinical shock, and 149 displayed no shock. After incorporating lactate into the analysis, 86 patients demonstrated no shock, 25 were classified as sub‐clinical shock, 91 were classified as occult shock, and 3 were characterized as overt shock. Each shock subcategory revealed a graded increase requiring LSI and transfusion. Initial CRM was associated with progression to shock (odds ratio = 0.97; p < .001) at an earlier time than SBP or LAC. Conclusions Initial CRM uncovers a clinically relevant subset of patients who are not detected by SBP and LAC. Our results suggest CRM could be used to more expeditiously identify injured patients likely to deteriorate to shock, with requirements for blood transfusion or procedural LSI.

Convertino, Victor A.↗

qSIEVE: Efficient qLDPC Memory via Systolic Movement in Atom Arrays

As quantum machines have scaled up in their number of qubits, significant research has turned towards increasing their fidelity with quantum error correction codes. Although promising results have been shown with the surface code, which only requires near-neighbor connections between qubits, the high qubit overhead of such local codes promises to be problematic. Consequently, recent work has explored non-local quantum LDPC (qLDPC) codes, which have good asymptotic encoding rates. Despite theoretical progress, hardware implementations of these codes have been a longstanding challenge. At the experimental level, demonstrations of movement based communication on atom arrays suggest this is a powerful new primitive to achieve non-local connectivity. Leveraging this, we present a protocol for implementing non-local qLDPC codes in hardware. Our protocol, qSIEVE, is a co-design of such codes with movement in atom arrays. qSIEVE defines a restricted family of qLDPC codes that can be implemented efficiently with systolic movement. We then quantify the utility of qSIEVE in the context of a complete fault tolerant architecture. We compare the cost of implementing benchmark programs in a standard, surface code only architecture and a mixed architecture where data is stored in qLDPC memory with qSIEVE and loaded to surface codes for computation.

Quantum error correction↗

Exposure to multiple ion beams, broadly representative of galactic cosmic rays, causes perivascular cardiac fibrosis in mature male rats

Long-duration space exploratory missions to the Earth’s moon and the planet Mars are actively being planned. Such missions will require humans to live for prolonged periods beyond low earth orbit where astronauts will be continuously exposed to high energy galactic cosmic rays (GCRs). A major unknown is the potential impact of GCRs on the risks of developing degenerative cardiovascular disease, which is a concern to NASA. A ground-based rat model has been used to provide a detailed characterization of the risk of long-term cardiovascular disease from components of GCRs at radiation doses relevant to future human missions beyond low earth orbit. Six month old male WAG/RijCmcr rats were irradiated at a ground-based charged particle accelerator facility with high energy ion beams broadly representative of GCRs: protons, silicon and iron. Irradiation was given either as a single ion beam or as a combination of three ion beams. For the doses used, the single ion beam studies did not show any significant changes in the known cardiac risk factors and no evidence of cardiovascular disease could be demonstrated. In the three ion beam study, the total cholesterol levels in the circulation increased modestly over the 270 day follow up period, and inflammatory cytokines were also increased, transiently, 30 days after irradiation. Perivascular cardiac collagen content, systolic blood pressure and the number of macrophages found in the kidney and in the heart were each increased 270 days after irradiation with 1.5 Gy of the three ion beam grouping. These findings provide evidence for a cardiac vascular pathology and indicate a possible threshold dose for perivascular cardiac fibrosis and increased systemic systolic blood pressure for complex radiation fields during the 9 month follow up period. The development of perivascular cardiac fibrosis and increased systemic systolic blood pressure occurred at a physical dose of the three ion beam grouping (1.5 Gy) that was much lower than that required to show similar outcomes in earlier studies with the same rat strain exposed to photons. Further studies with longer follow up periods may help determine whether humans exposed to lower, mission-relevant doses of GCRs will develop radiation-induced heart disease.

60 APPLIED LIFE SCIENCES↗

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition

Purpose: Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera. Methods: A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated. Results: The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth. Conclusion: The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

60 APPLIED LIFE SCIENCES↗

Antihypertensive effect of quinoa protein under simulated gastrointestinal digestion and peptide characterization

Abstract BACKGROUND Quinoa protein is a potential source of bioactive peptides. Although some studies have demonstrated its angiotensin converting enzyme (ACE) inhibitory properties, research into its in vivo effect on blood‐pressure regulation and peptide characterization remains limited. RESULTS Quinoa protein hydrolyzate (QPH) was prepared by simulated gastrointestinal digestion. QPH lowered the systolic blood pressure (SBP) and diastolic blood pressure (DBP) in spontaneously hypertensive model rats (SHRs) from 2 h to10 h after oral administration, effectively controlling blood pressure in these SHRs. An in vitro study showed that QPH is capable of inhibiting ACE activity. This was attributed to the activity of a number of low‐molecular‐weight peptides. With relatively high scores predicted by PeptideRanker, three promising bioactive peptides, FHPFPR, NWFPLPR, and NIFRPF, were further studied and their ACE‐inhibition effects were confirmed with IC 50 values of 34.92, 16.77, and 32.40 μM, respectively. A molecular docking study provided insights into the binding of ACE with peptides, and revealed that the presence of specific amino acids in the peptide sequence (Pro, Phe, and Arg at the C‐terminal, and Asn at the N‐terminal) could contribute to the interaction between ACE and peptides. CONCLUSION These results demonstrated the potential of QPH for the management of hypertension, which indicates that it could be a good candidate for inclusion in functional foods to control high blood pressure. © 2020 Society of Chemical Industry

Guo, Huimin↗

Hyperbolic string vertices

The string vertices of closed string field theory are subsets of the moduli spaces of punctured Riemann surfaces that satisfy a geometric version of the Batalin-Vilkovisky master equation. We present a homological proof of existence of string vertices and their uniqueness up to canonical transformations. Using hyperbolic metrics on surfaces with geodesic boundaries we give an exact construction of string vertices as sets of surfaces with systole greater than or equal to L with L ≤ 2 arcsinh 1. Intrinsic hyperbolic collars prevent the appearance of short geodesics upon sewing. The surfaces generated by Feynman diagrams are naturally endowed with Thurston metrics: hyperbolic on the vertices and flat on the propagators. For the classical theory the length L is arbitrary and, as L → ∞hyperbolic vertices become the minimal-area vertices of closed string theory

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Convex Programs for Minimal-Area Problems

The minimal-area problem that defines string diagrams in closed string field theory asks for the metric of least area on a Riemann surface with the condition that all non-contractible closed curves have length at least 2π. This is an extremal length problem in conformal geometry as well as a problem in systolic geometry. Here, we consider the analogous minimal-area problem for homology classes of curves and, with the aid of calibrations and the max flow-min cut theorem, formulate it as a local convex program. We derive an equivalent dual program involving maximization of a concave functional. These two programs give new insights into the form of the minimal-area metric and are amenable to numerical solution. We explain how the homology problem can be modified to provide the solution to the original homotopy problem.

97 MATHEMATICS AND COMPUTING↗

Spectral Bounds on Hyperbolic 3-Manifolds: Associativity and the Trace Formula

We constrain the low-energy spectra of Laplace operators on closed hyperbolic manifolds and orbifolds in three dimensions, including the standard Laplace--Beltrami operator on functions and the Laplacian on powers of the cotangent bundle. Our approach employs linear programming techniques to derive rigorous bounds by leveraging two types of spectral identities. The first type, inspired by the conformal bootstrap, arises from the consistency of the spectral decomposition of the product of Laplace eigensections, and involves the Laplacian spectra as well as integrals of triple products of eigensections. We formulate these conditions in the language of representation theory of PSL 2 (C) and use them to prove upper bounds on the first and second Laplacian eigenvalues. The second type of spectral identities follows from the Selberg trace formula. We use them to find upper bounds on the spectral gap of the Laplace--Beltrami operator on hyperbolic 3-orbifolds, as well as on the systole length of hyperbolic 3-manifolds, as a function of the volume. Further, we prove that the spectral gap λ 1 of the Laplace--Beltrami operator on all closed hyperbolic 3-manifolds satisfies λ 1 < 47.32. Along the way, we use the trace formula to estimate the low-energy spectra of a large set of example orbifolds and compare them with our general bounds, finding that the bounds are nearly sharp in several cases.

Bonifacio, James [University of Mississippi, MS (U↗

The mitochondrially targeted peptide elamipretide (SS-31) improves ADP sensitivity in aged mitochondria by increasing uptake through the adenine nucleotide translocator (ANT)

Aging muscle experiences functional decline in part mediated by impaired mitochondrial ADP sensitivity. Elamipretide (ELAM) rapidly improves physiological and mitochondrial function in aging and binds directly to the mitochondrial ADP transporter ANT. We hypothesized that ELAM improves ADP sensitivity in aging leading to rescued physiological function. We measured the response to ADP stimulation in young and old muscle mitochondria with ELAM treatment, in vivo heart and muscle function, and compared protein abundance, phosphorylation, and S-glutathionylation of ADP/ATP pathway proteins. ELAM treatment increased ADP sensitivity in old muscle mitochondria by increasing uptake of ADP through the ANT and rescued muscle force and heart systolic function. Protein abundance in the ADP/ATP transport and synthesis pathway was unchanged, but ELAM treatment decreased protein s-glutathionylation incuding of ANT. Mitochondrial ADP sensitivity is rapidly modifiable. This research supports the hypothesis that ELAM improves ANT function in aging and links mitochondrial ADP sensitivity to physiological function.

60 APPLIED LIFE SCIENCES↗

Superiority of compensatory reserve measurement compared with the Shock index for early and accurate detection of reduced central blood volume status

Shock index (SI) equals the ratio of heart rate (HR) to systolic blood pressure (SBP) with clinical evidence that it is more sensitive for trauma patient status assessment and prediction of outcome compared with either HR or SBP alone. We used lower body negative pressure (LBNP) as a human model of central hypovolemia and compensatory reserve measurement (CRM) validated for accurate tracking of reduced central blood volume to test the hypotheses that SI: (1) presents a late signal of central blood volume status; (2) displays poor sensitivity and specificity for predicting the onset of hemodynamic decompensation; and (3) cannot identify individuals at greatest risk for the onset of circulatory shock. We measured HR, SBP, and CRM in 172 human subjects (19–55 years) during progressive LBNP designed to determine tolerance to central hypovolemia as a model of hemorrhage. Subjects were subsequently divided into those with high tolerance (HT) (n = 118) and low tolerance (LT) (n = 54) based on completion of 60 mm Hg LBNP. The time course relationship between SI and CRM was determined and receiver operating characteristic (ROC) area under the curve (AUC) was calculated for sensitivity and specificity of CRM and SI to predict hemodynamic decompensation using clinically defined thresholds of 40% for CRM and 0.9 for SI. The time and level of LBNP required to reach a SI = 0.9 (~60 mm Hg LBNP) was significantly greater (p < 0.001) compared with CRM that reached 40% at ~40 mm Hg LBNP. Shock index did not differ between HT and LT subjects at 45 mm Hg LBNP levels. ROC AUC for CRM was 0.95 (95% CI = 0.94–0.97) compared with 0.91 (0.89–0.94) for SI (p = 0.0002). Despite high sensitivity and specificity, SI delays time to detect reductions in central blood volume with failure to distinguish individuals with varying tolerances to central hypovolemia.

60 APPLIED LIFE SCIENCES↗

H-GCN: A Graph Convolutional Network Accelerator on Versal ACAP Architecture

Recently Graph Neural Networks (GNNs) have drawn tremendous attentions due to their unique capability to extend the Machine Learning (ML) approaches to broadly defined applications with unstructured data, especially graphs. Comparing with other ML modalities, the acceleration of GNNs is as critical but even more challenging due to the irregularity and heterogeneity from graph typologies that together limit the performance. Existing efforts mainly focus on handling graphs’ irregularity, however, have not studied the heterogeneity. To this end, in this work, we propose H-GCN, a PL-AIE-based hybrid accelerator that leverages the emerging heterogeneity of Xilinx Versal ACAPs to achieve high-performance GNN inference. In particular, H-GCN partitions each graph into three subgraphs based on its inherent heterogeneity and processes them using PL and the newly emerged AIE respectively. To further improve the performance, we explore the sparsity support of AIE and develop an efficient density-aware method to map tiles of SpMM onto the systolic tensor array automatically. Compared with the current state-of-the-art GCN accelerator, HGCN achieves on average 1.5× speedups.

Zhang, Chengming↗

Bridging the Gap Between LLMs and LNS with Dynamic Data Format and Architecture Codesign

Deep neural networks (DNNs) have achieved tremendous success in the past few years. However, their training and inference demand exceptional computational and memory resources. Quantization has been shown as an effective approach to mitigate the cost, with the mainstream data types reduced from FP32 to FP16/BF16 and recently FP8 in the latest NVIDIA H100 GPUs. With increasingly aggressive quantization, however, the conventional floating-point formats suffer from limited precision in representing numbers around zero. Recently, NVIDIA demonstrated the potential of using a Logarithmic Number System (LNS) for the next generation of tensor cores. While LNS mitigates the hurdles in representing small numbers, in this work we observed a mismatch between LNS and the emerging Large Language Models (LLM), where LLM exhibits significant outliers when directly adopting the LNS format. In this paper, we present a data-format/architecture codesign to bright this gap. On the format side, we propose a dynamic LNS format to flexibly represent outliers at a higher precision, by exploiting asymmetry in the LNS representation and identifying outliers through a per-vector basis. On the architecture side, for demonstration, we realize the dynamic LNS format in a systolic array, which can handle the irregularity of the outliers at runtime. We implement our approach on an Alveo U280 FPGA as a prototype. Experimental results show that our design can effectively handle the outliers and resolve the mismatch between LNS and LLM, contributing to an accuracy improvement of 15.4% and 16% over the floating-point and the original LNS baselines, using four state-of-the-art LLM models. Our observation and design lay a solid foundation for the large-scale adoption of the LNS format in the next-generation deep learning hardware.

Haghi, Pouya↗

Acute total body ionizing gamma radiation induces long-term adverse effects and immediate changes in cardiac protein oxidative carbonylation in the rat

Radiation-induced heart disease presents a significant challenge in the event of an accidental radiation exposure as well as to cancer patients who receive acute doses of irradiation as part of radiation therapy. We utilized the spontaneously hypertensive Wistar-Kyoto rat model, previously shown to demonstrate drug-induced cardiomyopathy, to evaluate the acute and long-term effects of sub-lethal total body gamma irradiation at two, four, and fiftytwo weeks. We further examined irreversible oxidative protein carbonylation in the heart immediately following irradiation in the normotensive Wistar-Kyoto rat. Both males and females sustained weight loss and anemic conditions compared to untreated controls over a one-year period as reflected by reduced body weight and low red blood cell count. Increased inflammation was detected by elevated IL-6 serum levels selectively in males at four weeks. Serum cardiac troponin T and I analyses revealed signs of cardiomyopathy at earlier timepoints, but high variability was observed, especially at one year. Echocardiography at two weeks following 5.0Gy treatment revealed a significant decrease in cardiac output in females and a significant decrease in both diastolic and systolic volumes in males. Following 10.0Gy irradiation in the normotensive Wistar-Kyoto rat, the heart tissue showed an increase in total protein oxidative carbonylation accompanied by DNA damage indicated by an increase in γ-H2AX. Using proteomic analyses, we identified several novel proteins which showed a marked difference in carbonylation including those of mitochondrial origin and most notably, cardiac troponin T, one of the key proteins involved in cardiomyocyte contractility. Overall, we present findings of acute oxidative protein damage, DNA damage, cardiac troponin T carbonylation, and long-term cardiomyopathy in the irradiated animals.

59 BASIC BIOLOGICAL SCIENCES↗

FPGA Acceleration of GCN in Light of the Symmetry of Graph Adjacency Matrix

Graph Convolutional Neural Networks (GCNs) are widely used to process large-scale graph data. Different from deep neural networks (DNNs), GCNs are sparse, irregular, and unstructured, posing unique challenges to hardware acceleration with regular processing elements (PEs). In particular, the adjacency matrix of a GCN is extremely sparse, leading to frequent but irregular memory access, low spatial/temporal data locality and poor data reuse. Furthermore, a realistic graph usually consists of unstructured data (e.g., unbalanced distributions), creating significantly different processing times and imbalanced workload for each node in GCN acceleration. To overcome these challenges, we propose an end-to-end hardware-software co-design to accelerate GCNs on resource-constrained FPGAs with the features including: (1) A custom dataflow that leverages symmetry along the diagonal of the adjacency matrix to accelerate feature aggregation for undirected graphs. We utilize either the upper or the lower triangular matrix of the adjacency matrix to perform aggregation in GCN to improve data reuse. (2) Unified compute cores for both aggregation and transform phases, with full support to the symmetry-based dataflow. These cores can be dynamically reconfigured to the systolic mode for transformation or as individual accumulators for aggregation in GCN processing. (3) Preprocessing of the graph in software to rearrange the edges and features to match the custom dataflow. This step improves the regularity in memory access and data reuse in the aggregation phase. Moreover, we quantize the GCN precision from FP32 to INT8 to reduce the memory footprint without losing the inference accuracy. We implement our accelerator design in Intel Stratix10 MX FPGA board with HBM2, and demonstrate 1.3x-110.5x improvement in end-to-end GCN latency as compared to the state-of the-art FPGA implementations, on the graph datasets of Cora, Pubmed, Citeseer and Reddit.

Nair, Gopikrishnan R.↗

EMD-57033 Augments the Contractility in Porcine Myocardium by Promoting the Activation of Myosin in Thick Filaments

Sufficient cardiac contractility is necessary to ensure the sufficient cardiac output to provide an adequate end-organ perfusion. Inadequate cardiac output and the diminished perfusion of vital organs from depressed myocardium contractility is a hallmark end-stage of heart failure. There are no available therapeutics that directly target contractile proteins to improve the myocardium contractility and reduce mortality. The purpose of this study is to present a proof of concept to aid in the development of muscle activators (myotropes) for augmenting the contractility in clinical heart failure. Here we use a combination of cardiomyocyte mechanics, the biochemical quantification of the ATP turnover, and small angle X-ray diffraction on a permeabilized porcine myocardium to study the mechanisms of EMD-57033 (EMD) for activating myosin. We show that EMD increases the contractility in a porcine myocardium at submaximal and systolic calcium concentrations. Biochemical assays show that EMD decreases the proportion of myosin heads in the energy sparing super-relaxed (SRX) state under relaxing conditions, which are less likely to interact with actin during contraction. Structural assays show that EMD moves the myosin heads in relaxed muscles from a structurally ordered state close to the thick filament backbone, to a disordered state closer to the actin filament, while simultaneously inducing structural changes in the troponin complex on the actin filament. The dual effects of EMD on activating myosin heads and the troponin complex provides a proof of concept for the use of small molecule muscle activators for augmenting the contractility in heart failure.

59 BASIC BIOLOGICAL SCIENCES↗

Design and execution of a verification, validation, and uncertainty quantification plan for a numerical model of left ventricular flow after LVAD implantation

Left ventricular assist devices (LVADs) are implantable pumps that act as a life support therapy for patients with severe heart failure. Despite improving the survival rate, LVAD therapy can carry major complications. Particularly, the flow distortion introduced by the LVAD in the left ventricle (LV) may induce thrombus formation. While previous works have used numerical models to study the impact of multiple variables in the intra-LV stagnation regions, a comprehensive validation analysis has never been executed. The main goal of this work is to present a model of the LV-LVAD system and to design and follow a verification, validation and uncertainty quantification (VVUQ) plan based on the ASME V&V40 and V&V20 standards to ensure credible predictions. The experiment used to validate the simulation is the SDSU cardiac simulator, a bench mock-up of the cardiovascular system that allows mimicking multiple operation conditions for the heart-LVAD system. The numerical model is based on Alya, the BSC’s in-house platform for numerical modelling. Alya solves the Navier-Stokes equation with an Arbitrary Lagrangian-Eulerian (ALE) formulation in a deformable ventricle and includes pressure-driven valves, a 0D Windkessel model for the arterial output and a LVAD boundary condition modeled through a dynamic pressure-flow performance curve. The designed VVUQ plan involves: (a) a risk analysis and the associated credibility goals; (b) a verification stage to ensure correctness in the numerical solution procedure; (c) a sensitivity analysis to quantify the impact of the inputs on the four quantities of interest (QoIs) (average aortic root flow $Q^{avg}_{Ao}$, maximum aortic root flow $Q^{max}_{Ao}$, average LVAD flow $Q^{avg}_{VAD}$, and maximum LVAD flow $Q^{max}_{VAD}$; (d) an uncertainty quantification using six validation experiments that include extreme operating conditions. Numerical code verification tests ensured correctness of the solution procedure and numerical calculation verification showed a grid convergence index (GCI)95% <3.3%. The total Sobol indices obtained during the sensitivity analysis demonstrated that the ejection fraction, the heart rate, and the pump performance curve coefficients are the most impactful inputs for the analysed QoIs. The Minkowski norm is used as validation metric for the uncertainty quantification. It shows that the midpoint cases have more accurate results when compared to the extreme cases. The total computational cost of the simulations was above 100 [core-years] executed in around three weeks time span in Marenostrum IV supercomputer. This work details a novel numerical model for the LV-LVAD system, that is supported by the design and execution of a VVUQ plan created following recognised international standards. We present a methodology demonstrating that stringent VVUQ according to ASME standards is feasible but computationally expensive.

59 BASIC BIOLOGICAL SCIENCES↗