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Integrated Computational Materials Engineering (ICME) Capability Maturity Levels for Ecosystems Enabling Digital Transformation

Digital engineering (DE) and integrated computational materials engineering (ICME) are widely recognized as critical enablers of faster, more affordable, and more reliable aerospace systems. However, many organizations have struggled to realize the promised return on investment (ROI) from digital initiatives. A primary reason is the absence of a shared, decision-focused framework that distinguishes simple digitization of existing workflows from true digital transformation that fundamentally changes how engineering decisions are made. This paper introduces an ICME capability maturity framework that fills this gap. The framework defines six cumulative ICME capability maturity levels (CMLs), explicitly tied to decision authority, engineering integration, optimization, and uncertainty management across material, process, structure, and performance scales. It is designed to complement established readiness metrics such as technology readiness levels (TRLs), manufacturing readiness levels (MRLs), and integration readiness levels (IRLs), by addressing a missing dimension: the conditions required for model-informed decision authority across scales. A unifying figure and capability table illustrate the six-level ICME Capability Maturity Framework, showing how organizations progress from digitization—with limited or negative ROI—to true digital transformation, where ICME-enabled workflows deliver measurable improvements in decision quality, cycle time, risk reduction, and reuse. The framework is intended for both technical practitioners and executive leadership, providing a common language to assess current state, guide roadmaps, align software ecosystem investments, and set realistic expectations for digital transformation outcomes. A regulatory-relevant statement clarifying the relationship between ICME capability and existing certification frameworks is provided.

ICME

Atmospheric, Non-Combusting Droplet Sizing and Spray Imaging Results From a Non-Proprietary Aero Gas Turbine Engine Pressure Swirl Atomizer using Shadowgraphy and Planar Laser Scatter

Members from industry and federal agencies of the United States have developed a collaborating group focused on improving the understanding of the atomization processes common to gas turbine engines. The group is aimed on providing high quality data using x-ray diagnostics in the internal geometry and the near-field dense spray as well as optical diagnostics in the visible spectrum, downstream of the nozzle. This paper reports results from one of the two non-proprietary injectors designs from the group: the primary-secondary injector. In particular, we characterize the spray from only the primary, pressure-swirl atomizing circuit using water through the nozzle. We observed Sauter mean diameter decreased with increased water pressure drop across the nozzle. SMD was also collected at three axial distances and showed decreased size with distance from the nozzle. Planar laser sheet droplet scattering provided qualitative assessment of the spray. Higher water pressure drops provided better atomization than lower pressure drops. The addition of swirling air flow through the injector alleviates and improves the atomization quality, particularly at the lower water pressure drops.

optical diagnostics

Wide-ranging predictions of new stable compounds powered by recommendation engines

The computational search for new stable inorganic compounds is faster than ever, thanks to high-throughput density functional theory (DFT). However, stable compound searches remain highly expensive because of the enormous search space and the cost of DFT calculations. To aid these searches, recommendation engines have been developed. We conduct a systematic comparison of the performance of previously developed recommendation engines, specifically ones based on elemental substitution, data mining, and neural network prediction of formation enthalpy. After identifying ways to improve the recommendation engines, we find the neural network to be superior at recommending stable Heusler compounds. Armed with improved recommendation engines, we identify tens of thousands of compounds that are stable at zero temperature and pressure, now available in the Open Quantum Materials Database. We summarize this diverse pool of compounds, including the elusive mixed anion compounds, and two of their many applications: thermoelectricity and solar thermochemical fuel production.

Science & Technology - Other Topics

An Investigation Regarding the Effects of Volume Dynamics on Gas Turbine Engine Performance and Operability

This work explores the impact of adding volume dynamics to an electrified turbofan engine model. The zero-dimensional single-input single-output volume elements capture the physics of fluid compressibility of flow in the engine core gas path turbomachinery during transient operation with greater fidelity. Some background regarding the motivation for this effort is provided. A model of the volume element is developed from first principles. The baseline engine model is described and an explanation is given of the modifications made to incorporate the volume elements into the new model. Details of the simulated inputs, designed to elicit exaggerated dynamic responses and to facilitate comparison between the baseline and modified engine models, are explicated. The results of these simulations are presented and discussed, demonstrating that the transient performance and operability of the modified engine model, measured by parameters such as shaft speeds, thrust, and high-pressure compressor (HPC) stall margin, are impacted by the additional dynamics. Commentary is provided regarding potential explanations for the differences in behavior exhibited by the two models. Finally, suggestions are offered for future work that might improve the volume models developed in this effort and leverage the improved fidelity enabled by the modeling of turbomachinery volume dynamics.

Volume dynamics

Preliminary Findings of the Experimental Development Unit Cold Flow Test for a Generation Zero Nuclear Propulsion Engine

Nuclear thermal propulsion (NTP) technology will greatly benefit human travel to Mars by significantly shortening transit times, improving crew safety, and providing more mission flexibility than traditional chemical rockets. As part of DRACO follow-on work to develop, build, and fly a generation zero NTP engine, a full scale flight-like experimental design unit (EDU) reactor was constructed to collect sufficient on-ground performance data to characterize flow induced vibrations (FIV) of critical reactor structures/components, inform development of the engine and reactor control algorithm, and collect pressure drop and flow distribution data across the reactor. The fluid conditions for the test program were designed to achieve system responses equivalent to that of an operational engine through all phases of engine operation including reactor startup, mainstage operation, reactor shutdown, and reactor cooldown. Over 100 tests were executed, flowing either GN2 or GHe through the EDU at varying flow rates and pressures. This experiment provided early validation of flow behavior and vibration risks before nuclear testing, boosted critical subsystem TRLs, informed design iterations, and reduced future test costs. The steady-state flow parameters for the experiment were modeled in Ansys Thermal Desktop, allowing rapid tuning and experiment-informed updates to a flight-like test matrix. The EDU dynamic environment was characterized with accelerometers, strain gauges, and high-frequency pressure transducers all sampled at 20 kHz. While many narrow-band oscillations were identified, no significant FIV occurred; the reactor structural responses tend to be enveloped by typical launch vehicle ascent vibration environments (defined up to 2 kHz), although significant energy is also present at higher frequencies.

Flow Induced Vibration

Experimental Effects of Scaling on the Performance of Ion Rockets Employing Electron-Bombardment Ion Sources

A scaling program was undertaken to establish the relations between performance parameters and the size of the electron bombardment ion source. The experimental results of this investigation are the subject of this paper. Two geometrically similar sources, a 5- and a 20-cm-diameter beam source, were scaled from a 10-cm-diameter source to allow a performance comparison to be made. The three ion sources are compared for ion chamber characteristics and overall engine efficiency. The results of the chamber investigations are compared with scaling variations indicated by simple plasma theory. The effects of size on operating limits are also discussed. Mercury was used as the propellant in this investigation.

Power Supply

Diffraction-quality, ultraflexible protein single crystals engineered with DNA

DNA-functionalized colloidal nanoparticles assemble through flexible, nanoscale DNA hybridization interactions that limit atomic-level structural order. Here, we report a valence-centric strategy that enables DNA-bonded, protein single crystals with unconventional mechanical properties. An octameric enzyme, glutarate L-2-hydroxylase, was site- and number-selectively conjugated with eight self-complementary single-stranded DNA, yielding octavalent molecular bonds. The resulting conjugate assembled into the designed body-centered tetragonal crystals that diffracted to 1.42- to 2.61-angstrom resolution, with contacts mediated by B-form DNA helices spanning 17 to 25 angstroms. Increasing oligonucleotide length induces anisotropic lattice expansion while preserving atomic periodicity, even with partial DNA occupancy. Mechanistic studies suggest that the dynamic motion of unhybridized DNA facilitates crystallization, analogous to fluctuating electron clouds in atomic bonding. Compared with native protein crystals, DNA-hybridized crystals are 23-fold softer. These results challenge the assumption that flexibility is incompatible with structural order and establish a programmable framework for biomolecular crystallization and nanomaterials engineering with atomic precision.

Han, Zhenyu [Department of Chemistry, Northwestern