Contributions to HiLiftPW-3 Using Structured, Overset Grid Methods

The High-Lift Common Research Model (HL-CRM) and the JAXA Standard Model (JSM) were analyzed computationally using both the OVERFLOW and LAVA codes for the third AIAA High-Lift Prediction Workshop. Geometry descriptions and the test cases simulated are described. With the HL-CRM, the effects of surface smoothness during grid projection and the effect of partially sealing a flap gap were studied. Grid refinement studies were performed at two angles of attack using both codes. For the JSM, simulations were performed with and without the nacelle/pylon. Without the nacelle/pylon, evidence of multiple solutions was observed when a quadratic constitutive relation is used in the turbulence modeling; however, using time-accurate simulation seemed to alleviate this issue. With the nacelle/pylon, no evidence of multiple solutions was observed. Laminar-turbulent transition modeling was applied to both JSM configuration, and had an overall favorable impact on the lift predictions

OVERFLOW Contribution to HiLiftPW-3

We plan to perform the following sets of computations: For all our contributions (except where stated) Code: OVERFLOW, Turbulence model: SAnegRCQCR2000. - 1. Results will be submitted for both the full chord flap gap (Case 1a) and partially-sealed Chord Flap gap (Case 1c): 1. Grid Refinement Study; 2. Grids: structured overset grids supplied by HiLiftPW committee; 3. Connectivity: Domain Connectivity Framework, DCF. - 2. Results will be submitted for JAXA Standard Model and Nacelle/Pylon Off (Case 2a), Nacelle/Pylon On (Case 2c): 1. Alpha Study; 2. Grids: structured overset grids supplied by HiLiftPW committee; 3. Connectivity: Pegasus 5 (Peg5). - 3. A study of the effects of different connectivity paradigms: 1. DCF vs Peg5 for HLCRM cases; 2. DCF vs. C3P (NASA Ames) vs. Peg5 for JSM cases; 3. JSM grids will be the focus where we will hopefully see some type of trends with reference to wind tunnel data. - 4. Adaption cases will be attempted for (and submitted where appropriate): 1. Cases 1c,1d: HLCRM; 2. Cases 2c and 2d: JSM; 3. Grid: Near Body grids provided by committee, OffBody grids Cartesian; 4. AMR NearBody and OffBody Adaption. - 5. Case 3 Turbulence model verification study: 1. Grid: Series of 3 finest grids as defined on http://turbmodels.larc.nasa.gov/airfoilwakeverif.html; 2. Turbulence models: SAneg and SAneg RCQCR2000. OVERFLOW 2.2 is a Reynolds-averaged Navier-Stokes (RANS) code developed by NASA..

Contributions to the Sixth Drag Prediction Workshop Using Structured, Overset Grid Methods

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143028/1/1.C034486.pd

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

OVERFLOW Contribution to HiLiftPW-3

No abstract availabl

Contributions to the 6th AIAA CFD Drag Prediction Workshop Using Structured Grid Methods

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143019/1/6.2017-0960.pd