{"id":4847,"date":"2021-03-19T11:15:43","date_gmt":"2021-03-19T15:15:43","guid":{"rendered":"https:\/\/hemi.jhu.edu\/mseeura\/?page_id=4847"},"modified":"2021-06-25T12:21:48","modified_gmt":"2021-06-25T16:21:48","slug":"research-strategy","status":"publish","type":"page","link":"https:\/\/hemi.jhu.edu\/mseeura\/research-strategy\/","title":{"rendered":"Research Strategy"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text]<\/p>\n

MSEE URA RESEARCH STRATEGY<\/span><\/h4>\n

[\/vc_column_text][vc_single_image image=”5450″ img_size=”full” alignment=”center”][vc_empty_space][\/vc_column][\/vc_row][vc_row css=”.vc_custom_1616167765640{background-color: #f1f1f1 !important;}”][vc_column][vc_empty_space][vc_column_text]<\/p>\n

See it<\/h4>\n

Experimental studies of materials in WMD-relevant environments (such as conventional fireballs, nuclear fireballs, photon-induced blow-off, plasmas, and warm dense matter) are exceptionally challenging but are vital for understanding and ultimately controlling material-WMD interactions. These environments may include extreme temperatures, pressures, and energies; they may evolve rapidly; and they may span a broad range of relevant time and length scales. Throughout the URA, we will leverage our prior expertise in state-of-the-art\u00a0in situ<\/em>\u00a0characterization and analysis to develop new and innovative optical, X-ray, and proton-based experimental methods. Part of this effort will include unique compressed sensing techniques for maximizing the data obtained from the experiments. In addition, we will use inverse uncertainty quantification (iUQ) to focus our experiments on the aspects of materials behavior and chemical reactions which improve the confidence of our predictions the most. Lastly, we will automate our analysis of high-dimensional optical and x-ray data through machine learning (ML).<\/p>\n

[\/vc_column_text][vc_empty_space][\/vc_column][\/vc_row][vc_row][vc_column][vc_empty_space][vc_column_text]<\/p>\n

Understand it<\/h4>\n

Models and simulations are crucial for understanding the behavior of materials in WMD-relevant environments and the fundamental mechanisms that govern their behavior. They are also crucial for developing materials with improved properties. However, the environments are challenging for simulations, so we will leverage our experimental observations to focus our computational efforts on the most important mechanisms, time scales, and length scales. As we\u00a0understand<\/em>\u00a0the fundamental mechanisms more completely, we will predict the response of materials to extreme events more effectively. We will leverage our cross-cutting uncertainty quantification (UQ) effort to characterize the fidelity of our simulations and predictions, and we will identify those aspects of the models where improvements will enable the greatest increases in confidence in their outputs. Ultimately, we will transition the most promising diagnostic tools and models to applied DTRA researchers and other members of our Government and Corporate Affiliates Program (GCAP) for use in restricted environments.<\/p>\n

[\/vc_column_text][vc_empty_space][\/vc_column][\/vc_row][vc_row css=”.vc_custom_1616167850463{background-color: #f1f1f1 !important;}”][vc_column][vc_empty_space][vc_column_text]<\/p>\n

Control it<\/h4>\n

Having\u00a0seen<\/em>\u00a0and\u00a0understood<\/em>\u00a0the relevant mechanisms and behaviors of materials, we will harness them through appropriate\u00a0control<\/em>\u00a0of the composition, processing, and architecture of materials to achieve improved performance in WMD applications. This is a potentially immense task as the range of possible parameters is huge, but we will reduce it to manageable proportions by utilizing our understanding of fundamental mechanisms and using our iUQ methodology to identify parameters that are most critical to controlling materials behavior. The UQ approach will enable us to quantify not only the\u00a0typical<\/em>\u00a0materials behavior, but also the\u00a0range<\/em>\u00a0of behaviors that can be expected. DTRA can then use this data to increase the confidence of their simulations that provide reach-back support to decision-makers in the field.<\/p>\n

[\/vc_column_text][vc_empty_space][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"

[vc_row][vc_column][vc_column_text] MSEE URA RESEARCH STRATEGY [\/vc_column_text][vc_single_image image=”5450″ img_size=”full” alignment=”center”][vc_empty_space][\/vc_column][\/vc_row][vc_row css=”.vc_custom_1616167765640{background-color: #f1f1f1 !important;}”][vc_column][vc_empty_space][vc_column_text] See it Experimental studies of materials in WMD-relevant environments…<\/p>\n","protected":false},"author":28,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-4847","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/hemi.jhu.edu\/mseeura\/wp-json\/wp\/v2\/pages\/4847","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hemi.jhu.edu\/mseeura\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/hemi.jhu.edu\/mseeura\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/hemi.jhu.edu\/mseeura\/wp-json\/wp\/v2\/users\/28"}],"replies":[{"embeddable":true,"href":"https:\/\/hemi.jhu.edu\/mseeura\/wp-json\/wp\/v2\/comments?post=4847"}],"version-history":[{"count":8,"href":"https:\/\/hemi.jhu.edu\/mseeura\/wp-json\/wp\/v2\/pages\/4847\/revisions"}],"predecessor-version":[{"id":6774,"href":"https:\/\/hemi.jhu.edu\/mseeura\/wp-json\/wp\/v2\/pages\/4847\/revisions\/6774"}],"wp:attachment":[{"href":"https:\/\/hemi.jhu.edu\/mseeura\/wp-json\/wp\/v2\/media?parent=4847"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}