Back to Company SearchSBIR-STTR-Success: Sentient Science (Sentient Corp.)
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Company
Portfolio Data
SENTIENT SCIENCE CORPORATION
UEI: KELCA1NLRN88
Number of Employees: 32
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
SBIR/STTR Involvement
Year of first award: 2002
43
Phase I Awards
24
Phase II Awards
55.81%
Conversion Rate
$5,151,369
Phase I Dollars
$19,319,470
Phase II Dollars
$24,470,838
Total Awarded
Success Stories
See what our company has achieved through SBIR/STTR funding.
Awards
DigitalClone Fretting Fatigue Life Prediction
Amount: $239,377 Topic: N25B-T032
The U.S. Navy is seeking an advanced fretting fatigue life prediction method for naval aerospace applications that advances the science, physics-based modeling & simulation (M&S), and mitigation techniques for fretting fatigue damage to improve durability, reliability, and performance in naval aero-structural applications. Fretting is a wear phenomenon that occurs when two surfaces in contact undergo small oscillatory motions with respect to one another. This small relative motion results in slippage in the outer regions of two contacting surfaces, where the shear force is sufficient to overcome frictional resistance. High points or asperities of the mating surfaces in the slip zone adhere to each other, resulting in the formation of shallow pits and a powdery debris (fretting wear). Microcracks can be initiated by the shear stress present in the slip zone within the first several thousand cycles. Since these cracks are usually not observable during operation, the need for a strategy for predicting their formation and propagation becomes apparent. Fretting fatigue is particularly detrimental in gearbox housing and assemblies and in various structural joints, where the combination of high cyclic loads, harsh environmental conditions (e.g., vibrations, thermal cycling), and material properties lead to accelerated degradation. In response to U.S. Navy SBIR Topic N25B-T032, Sentient proposes to utilize its DigitalClone for EngineeringTM (DCE) modeling technology for fretting fatigue applications. It is well recognized that initiation of fatigue failure generally occurs by nucleation and propagation of critical micro-cracks with sizes ranging from several micrometers to a few hundred micrometers. The growth of these cracks does not follow the conventional linear elastic fracture mechanics (LEFM) approach. Therefore, in order to obtain a reliable life prediction model, a physics-based model is needed to analyze the fatigue crack nucleation and short crack growth. During Phase I, Sentient is proposing to further develop our DCE modeling software to include the features required for fretting fatigue analysis including debris (captured in contact zone) modeling, corrosion effects, and microstructure modeling relevant to fretting fatigue applications. This model not only accounts for the effect of microstructure on the fretting fatigue crack creation and early growth, but also predicts the effect of presence of debris and corrosion on the fatigue life of the structure. In Phase I, material selection will be done through communication with Navy TPOCs and Aerospace OEMs for fretting fatigue in aerospace applications. Specimen manufacturing and coupon testing will be performed as part of Phase II. In Phase II, we will implement coupon and component physical testing for validation of our improved DCE modeling tool through collaboration with aerospace OEMs.
Tagged as:
STTR
Phase I
2026
DOD
NAVY
In-Situ Additive Manufacturing Tracking and Modification with DC-IM
Amount: $1,249,624 Topic: AFX236-DPCSO1
Additive manufacturing (AM) has drawn interest in the US Air Force owing to its high flexibility in fabricating complex geometries for significant component performance improvements, which results in great reductions in labor cost, production time, and co
Tagged as:
SBIR
Phase II
2023
DOD
USAF
An Integrated Software Package for Studying Structure-Property-Processing Relationships in Material Systems / Topic 14A
Amount: $199,934 Topic: C53-14a
The identification of structure-property-processing relationships require dynamical models that can access multitude of length spanning nanometers to microns and timescales spanning picoseconds to seconds. Despite its widespread availability of a variety of open source and commercial codes as well as their usage in various flavors, the predictive power of molecular dynamics (MD) is severely limited. Each flavor of MD therefore has a ceiling limit, which severely impedes its predictive power. Sentient proposes multi-fidelity scale bridging framework that provide users with the capabilities to train and develop their own classical atomistic and coarse-grained interatomic potentials (force fields) for molecular simulations. The framework will combine the accuracy and flexibility of electronic structure calculations with the speed of classical potentials by merging and exploiting the best insights from the fields of machine learning (ML), advanced optimization, and atomistic simulations. The multiscale framework will seamlessly and efficiently describe material properties and dynamical phenomena for broad class of materials at atomistic resolution over mesoscopic time and length scales without compromising the accuracy. In phase 1, Sentient will demonstrate a software package, that incorporates model development, molecular simulations, and data analysis in one user-friendly package, providing extremely rapid in-silico design and optimization capability and as such is expected to accelerate the technological advancement and industrial manufacturing through materials design and process optimization. The proposed software enables end users to develop accurate materials models across multiple length/timescales for a wide range of materials. The framework will be used for identifying structure- property-processing relationships in various material classes at an unprecedented pace; a successful implementation, and commercialization of this tool will drastically reduce the financial costs, and time required for developing new materials for emerging platforms in numerous facets of technology. Selected applications for the software include but not limited to: energy storage, batteries, quantum computing, semiconductors, polymers, advanced lubricants, rocket fuels
Tagged as:
SBIR
Phase I
2022
DOE
Physics-Based Modeling of Rolling/Sliding Contact Fatigue Life
Amount: $574,552 Topic: A19-140
Physics based modeling is required for an accurate prediction of bearing life. The key challenge of developing an accurate prediction model is the development of a multi-scale physics model that accounts for the kinematics and dynamics of bearing operation, material microstructure from latest bearing manufacturing processes, surface finish and residual stress of the final components, and the thermomechanical stress. Sentient developed multiscale physics-based models over several years to predict the fatigue behavior of mechanical components such as bearings at the microstructural level. In Phase I, Sentient demonstrated the approach to predict rolling contact fatigue life at a coupon level. Under Phase II, Sentient will demonstrate the modeling prediction on a component level at different bearing configurations, surface finishes, loading conditions, lubrication and more. Multiple set of tools at multiple temporal and spatial scales will be used to perform the simulations and to predict the bearing fatigue life. Model capabilities will be enhanced to account the effect of thermomechanical stresses. In Phase II, Sentient will partner with Rolls-Royce (RR), The University of Akron (UA), and Napoleon Engineering Services (NES) to validate the DC model on rolling element bearings under operating conditions of limited lubrication. Multiple bearing case studies with different bearing configurations (ball and roller bearing), materials (M50, M50 NiL, 52100), surface finishes, and operating conditions will be tested and simulated under rolling contact fatigue life. Bearing Analysis Tool (BAT) will be used to conduct multibody dynamic simulation of rolling element bearings to generate time histories of the component motions and contact details of deep groove ball bearing and cylindrical roller bearing. There are four main technical objectives to be achieved in Phase II.
Tagged as:
SBIR
Phase II
2022
DOD
ARMY
Rolling/Sliding Contact Fatigue Life Physics and Modeling
Amount: $166,728 Topic: A19-140
In response to Army topic A19-140, Sentient Science proposes to incorporate its DigitalClone modeling technology to predict the life of high-end precision bearings. For an accurate prediction of life, a physics-based model is required which captures the kinematics and dynamics of bearings operation, considers surface characteristics, mechanical properties, and material microstructure. In Phase 1, Sentient will demonstrate their extensively validated and commercially available predictive suite of computational modeling tools called DigitalClone. Sentient Science’s DigitalClone technology enables evaluation of bearing life characteristics in real-life application scenarios. Sentient’s DigitalClone technology is enriched with a multi-body bearing dynamics simulation tool specialized for analyzing rolling element bearings. The bearing analysis tool calculates the dynamic motion of all the components inside bearings, contact details for the interaction between the components, and their aggregate response as a single unit. The DigitalClone capability will be further developed to incorporate the effect of thermomechanical influences on bearing internal clearances and in turn the roller-raceway contact pressure in order to reliably predict the performance of rolling element bearings.
Tagged as:
SBIR
Phase I
2020
DOD
ARMY
Sentient Science - A Multiscale Modeling Suite for Process and Microstructure Prediction in Metal Additive Manufacturing
Amount: $749,602 Topic: T12
In the Phase I period, Sentient upgraded its DigitalClone for Additive Manufacturing (AM) technology and successfully demonstrated and validated its ldquo;Process modelrdquo; and ldquo;Microstructure modelrdquo; for simulating metal AM processes. Sentient has partnered with University of Nebraska ndash; Lincoln for model validation.Specifically, Sentient has implemented a new ldquo;Process modelrdquo; to predict part-level residual stress and distortion for parts built using AM processes. The new model shows high simulation efficiency and accuracy. In addition, Sentient has improved the simulation speed of its ldquo;Microstructure modelrdquo; by 100% for predicting the grain structure and porosity.The proposed DigitalClone for Additive Manufacturing (DCAM) simulation suite will fill the technical gap NASA is currently facing, and meetnbsp;NASArsquo;s requirement very well. The proposed solution allows NASA to: 1) simulate the part-level distortion and residual stress with respect to various key process parameters; 2) simulate the microstructurenbsp;of as-built AM components with respect to key parameters and locations of interest; and 3) simulate the fatigue performance of as-built AM components at specific mechanical loading conditions. This physics-based simulation suite has been well demonstrated in different AM platforms (i.e. powder bed fusion and direct energy deposition) and several alloys systems that NASA is interested in. Those materials include Inconel 625, Inconel 718, 17-4 PH, 15-5 PH stainless steel, Ti64, and AlSi10Mg alloy. Additionally, the simulation suite can be applied to any new alloy with minimum calibration needed. This physics-based simulation suite directly benefits NASA via allowing computational testing for new component design, new materials, and new process, which will significantly reduce cost and time compared to conventional physical testing.In the Phase II effort, Sentient will focus on developingnbsp;of prototype softwarenbsp;and further validatingnbsp;different materials and components.nbsp;nbsp;
Tagged as:
STTR
Phase II
2020
NASA
Fatigue Prediction for Additive Manufactured (AM) Metallic Components
Amount: $139,700 Topic: N19B-T026
Sentient proposes to develop a physics-based integrated computational materials engineering (ICME) framework (DigitalClone® Additive) to support the rapid qualification of AM components, including microstructural features, and macro-level fatigue performance. Sentient will apply their extensive experience with the DigitalClone technology to conduct multiscale modeling of AM process and resulting microstructure and fatigue life. Sentient’s DigitalClone is a physics-based computational modeling and design framework that simulates the microstructure of different components and their behavior, calculates internal stresses caused by different applied loading conditions, accumulates internal damages resulting in crack nucleation and propagation, and investigates the performance and life prediction. In Phase I, Sentient will demonstrate the technical feasibility of reconstructing AM microstructure, predicting fatigue life, and detailing the plans to integrate different modules for predicting fatigue performance of AM components. Specifically, in the Phase I base period, microstructure of different AM “dogbone” coupons will be simulated and validated against physical testing. Then, the microstructure domain will be converted to finite element-based domain and mesh, followed by finite element analysis of mechanical response uniaxial tensile test in this project.
Tagged as:
STTR
Phase I
2020
DOD
NAVY
Development of In-Process Monitoring Closed-Loop Feedback for Use in Aluminum Alloy Additive Manufacturing (AM) Applications
Amount: $560,069 Topic: A17-003
The overall goal of this project is to develop an in-process defect monitoring and correction technique for additive manufacturing (AM) of aluminum alloy to improve repeatability for geometric dimensions, material properties, and quality. In Phase I, Sentient collaborated with Johns Hopkins University Applied Physics Lab, and successfully completed all proposed tasks demonstrating two key capabilities: 1) in-situ defect monitoring capability using an infrared (IR) camera, and 2) defect correction capability using optimized AM process parameters through advanced modeling and simulation. The goal of Phase II is to develop the prototype of in-process defect monitoring and correction close-loop feedback system to optimize AM process for flaw control and defect correction. The in-situ defect monitoring capability and advanced simulation capability demonstrated in Phase I will be integrated in Matsuura LUMEX series powder bed fusion platform to demonstrate real-time close-loop feedback control capability. A comprehensive testing (e.g. microstructure, yield strength, fatigue life) will be performed on coupons made by the new AM system to demonstrate the improved part quality compared to baseline properties of as-build AM parts or conventionally sand casted parts. Finally, AM components (i.e. full-size gearbox) will be fabricated using prototype of the new AM system.
Tagged as:
SBIR
Phase II
2019
DOD
ARMY
Innovative Processing Techniques for Additive Manufacture of 7000 Series Aluminum Alloy Components
Amount: $124,940 Topic: N18A-T005
To address the needs of Navy to successfully produce 7000 series aluminum alloy components, Sentient proposes to develop a hybrid additive manufacturing (AM) process for this topic. Hybrid AM use a secondary process (e.g. peening, burnishing) along with primary AM process to tightly control thermal profile and stress evolution locally and globally, resulting enhanced part quality (e.g. negligible distortion, free of cracks, full dense).
Tagged as:
STTR
Phase I
2018
DOD
NAVY
Sentient Science - A Multiscale Modeling Suite for Process and Microstructure Prediction in Metal Additive Manufacturing
Amount: $124,729 Topic: T12
In response to NASA’s topic T12.02 of “Extensible Modeling of Metallurgical Additive Manufacturing Processes”, Sentient proposes to incorporate its DigitalClone technique to develop a multiscale and multiphysics computational modeling suite to predict comprehensive outcomes from AM building processes, including geometrical accuracy, and resulting microstructure and defects. Figure 1 shows the proposed framework for the multiscale modeling suite. The process model will first predict the microscale thermal evolution in respect of various parameters. The temperature results will feed a subsequent macroscale model for prediction of stress and distortion at part scale. Moreover, the predicted thermal history and distribution will feed subsequent microstructure model to further predict the micro-scale features including grain morphology and porosity. The proposed computational modeling framework allows a comprehensive prediction and understanding of the metal AM process at multiple levels.In Phase I, Sentient will upgrade and demonstrate DigitalClone’s capability to integrate process-microstructure simulation for metal AM process. Specifically, selective laser melting of IN 718 alloy will be used for development and demonstration purposes in Phase I. AM coupons with different geometries will be fabricated by Selective Laser Melting (SLM) at different parameters. DigitalClone will be used to simulate all different scenarios of coupons made from IN718 alloys, and predict temperature, stress, part distortion, and grain structure. Materials characterization will be performed on the coupons to examine geometrical accuracy, microstructure, residual stress, all of which will be used to validate the DigitalClone model. In Phase II, different materials and AM platforms and more complex geometrical components will be tested for model validation. Additionally, close-loop optimization framework will be explored for improving geometrical design and microstructure features.
Tagged as:
STTR
Phase I
2018
NASA