Further development of hybrid propulsion systems requires a deeper understanding of the complex physicochemical mechanisms governing its combustion performance. A tunable diode laser absorption tomography (TDLAT) method was developed for investigating the thermochemical processes at the nozzle exit of an oxygen/Poly Methyl MethAcrylate (PMMA) hybrid rocket motor. Firing tests were conducted for different oxidizer mass fluxes ranging from 2.73 to 3.51 g/ (cm2·s). A distributed feedback (DFB) laser was tuned to cover three H2O absorption lines near 2.5 μm, using scanned-wavelength direct absorption (DA) mode with 2.0 kHz repetition rate. Under an assumption of cylindrical symmetry, a Radon transformation was applied to yield radially- and time- resolved absorption coefficient, from which the radial distribution of temperature and H2O partial pressure were reconstructed. Based on the Taylor series method (TSM), measurement uncertainty was analyzed in detail considering line-strength uncertainty, Voigt fitting residuals and Radon transformation. Finally, the radial distribution and dynamic variations of both temperature and H2O partial pressure were obtained in all firing tests, both the constructed results show measurement sensitivity to chemical kinetic progress and oxidizer mass flux changes. Our experimental results highlight the capability of TDLAT to characterize combustion processes of hybrid rocket motors.
A mid-infrared TDLAS sensor near 2.5μm was designed for time-resolved measurements of temperature and water vapor partial pressure at the nozzle exit of a laboratory-scale hybrid rocket motor. Several previously used H2O transitions within 2.4-2.9μm were thoroughly investigated, and a line-pair containing three transitions (4029.52 cm-1 , 4030.51 cm-1 and 4030.73 cm-1 ) was selected for the optimal overall properties like strong absorbance, sufficient temperature sensitivity, single laser scan, high immunity from the ambient H2O transitions and low measurement uncertainty affected by temperature over the range of 1500K-2500K. Firing tests were conducted on an oxygen/paraffin-fueled hybrid rocket motor operating at oxygen/fuel ratios (O/Fs) of 3.10, 2.77 and 2.88, corresponding to average combustion pressures of 1.91MPa, 2.09MPa and 2.38MPa. A distributed feedback (DFB) laser tuned repetitively at 2kHz was used as the light source, and simultaneously the transmitted spectra were detected at a 2MHz sampling rate. Finally, a 4.5ms time-scale variations of temperature and H2O partial pressure were captured by TDLAS sensor. Uncertainty analysis was made in detail based on average temperature (1929.8K, 1926.5K, and 1990.7K) and average H2O partial pressure (0.237MPa, 0.253MPa, and 0.285MPa), leading to temperature uncertainty of around 2.24% and partial pressure uncertainties of around 3.80%, 3.79% and 4.04% respectively. The time-resolved measurement results and small measurement uncertaintiesindicate that TDLAS has the potential to evaluate the combustion performance of hybrid rocket motor
Allogenic hematopoietic stem cell transplant (HCT) is a curative therapy for acute myeloid leukemia (AML). Relapse after HCT is the most common cause of treatment failure and is associated with poor prognosis. Early identification of which patients are at elevated risk of relapse may justify use of aggressive post-HCT treatment options, potentially preventing relapse and treatment failure. In this study, our goal was to predict relapse after HCT in AML patients using quantitative features extracted from digitized Wright-Giemsa stained posttransplant aspirate smears. We collected 39 aspirate specimens from a cohort of 39 AML patients after HCT, of which 25 experienced relapse, while 14 did not. Our approach comprised the following main steps. First, a deep learning model was developed to segment myeloblasts, a cell type in bone marrow that accumulates and characterizes AML. A total of 161 texture and shape descriptors were then extracted from these segmented myeloblasts. The top eight predictive features were identified using a Wilcoxon rank sum test over 100 iterations of 3-fold cross validation. A model was subsequently built employing these features and yielded an average area under the receiver operating characteristic curve of 0.80±0.05 in cross validation. The top eight features include four Haralick texture features and four fractal dimension features. The texture features appear to characterize chromatin patterns in myeloblasts while the fractal features quantify morphological irregularity and complexity of myeloblasts, in alignment with findings previously reported for AML patients post-treatment.
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