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NASA NTRS2015

The Integrated Medical Model: A Probabilistic Simulation Model Predicting In-Flight Medical Risks

The Integrated Medical Model (IMM) is a probabilistic model that uses simulation to predict mission medical risk. Given a specific mission and crew scenario, medical events are simulated using Monte Carlo methodology to provide estimates of resource utilization, probability of evacuation, probability of loss of crew, and the amount of mission time lost due to illness. Mission and crew scenarios are defined by mission length, extravehicular activity (EVA) schedule, and crew characteristics including: sex, coronary artery calcium score, contacts, dental crowns, history of abdominal surgery, and EVA eligibility. The Integrated Medical Evidence Database (iMED) houses the model inputs for one hundred medical conditions using in-flight, analog, and terrestrial medical data. Inputs include incidence, event durations, resource utilization, and crew functional impairment. Severity of conditions is addressed by defining statistical distributions on the dichotomized best and worst-case scenarios for each condition. The outcome distributions for conditions are bounded by the treatment extremes of the fully treated scenario in which all required resources are available and the untreated scenario in which no required resources are available. Upon occurrence of a simulated medical event, treatment availability is assessed, and outcomes are generated depending on the status of the affected crewmember at the time of onset, including any pre-existing functional impairments or ongoing treatment of concurrent conditions. The main IMM outcomes, including probability of evacuation and loss of crew life, time lost due to medical events, and resource utilization, are useful in informing mission planning decisions. To date, the IMM has been used to assess mission-specific risks with and without certain crewmember characteristics, to determine the impact of eliminating certain resources from the mission medical kit, and to design medical kits that maximally benefit crew health while meeting mass and volume constraints.

Risk Analysis↗

NASA NTRS2015

The Integrated Medical Model: A Probabilistic Simulation Model for Predicting In-Flight Medical Risks

Risk Analysis↗

NASA NTRS2013

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

The mission of the National Aeronautics and Space Administration’s (NASA) human research program is to advance safe human spaceflight. This involves conducting experiments, collecting data, and analyzing data. The data are longitudinal and result from a relatively few number of subjects; typically 10 – 20. A longitudinal study refers to an investigation where participant outcomes and possibly treatments are collected at multiple follow-up times. Standard statistical designs such as mean regression with random effects and mixed–effects regression are inadequate for such data because the population is typically not approximately normally distributed. Hence, more advanced data analysis methods are necessary. This research focuses on four such methods for longitudinal data analysis: the recently proposed linear quantile mixed models (lqmm) by Geraci and Bottai (2013), quantile regression, multilevel mixed–effects linear regression, and robust regression. This research also provides computational algorithms for longitudinal data that scientists can directly use for human spaceflight and other longitudinal data applications, then presents statistical evidence that verifies which method is best for specific situations. This advances the study of longitudinal data in a broad range of applications including applications in the sciences, technology, engineering and mathematics fields.

Feiveson, Alan↗

NASA NTRS2006

Modeling Chemical Growth Processes in Titan's Atmosphere: 1. Theoretical Rates for Reactions between Benzene and the Ethynyl (C2H) and Cyano (CN) Radicals at Low Temperature and Pressure

Density functional theory calculations at the B3LYP/6-31+G** level were employed to characterize the critical points for adducts, isomers, products, and intervening transition states for the reactions between benzene and the ethynyl (C2H) or cyano (CN) radicals. Both addition reactions were found to have no barriers in their entrance channels, making them efficient at the low temperature and pressure conditions that prevail in the haze-forming region of Titan's atmosphere as well as in the dense interstellar medium (ISM). The dominant products are ethynylbenzene (C6H5C2H) and cyanobenzene (C6H5CN). Hydrogen abstraction reactions were also characterized but found to be non-competitive. Trajectory calculations based on potentials fit to about 600 points calculated at the ROMP2/6-31+G** level for each interaction surface were used to determine reaction rates. The rates incorporated any necessary corrections for back reactions as ascertained from a multiwell treatment used to determine outcome distributions over the range of temperatures and pressures pertinent to Titan and the ISM and are in good agreement with the limited available experimental data.

Woon, David E.↗

NASA NTRSDate not supplied

NASA Omics Archive Project

The space environment consists of a complex set of hazards including altered gravity, radiation, psychological/physiological stress, isolation, and confinement leading to complex biological responses. Advances in biotechnology capabilities offer considerable potential to provide novel insight into those responses as well as innovative diagnostic, treatment, and countermeasure solutions for astronauts as NASA begins to travel beyond low Earth orbit. Omics data (genomics, transcriptomics, proteomics, etc.) is one example that can provide NASA with critical knowledge of how a crewmember’s genetics, environment, and lifestyle can be used to develop individualized approaches for disease prevention, advance diagnostics, and improve treatment strategies. NASA ventured into the field of omics on human subjects with the successful completion of the NASA Twins Study which was the first step in mapping the multi-omic profile of astronauts to understand and mitigate the health consequences of spaceflight. The Human Research Program aims to build upon the success of the Twins Study with the NASA Omics Archive flight study, establishing a longitudinal biospecimen archive and efficiently generating a comprehensive high-quality multi-omic dataset from astronauts for the purpose of studying molecular, metabolic, and microbial changes associated with longduration spaceflight missions. The goal is to facilitate scientific and medical research community efforts to characterize and mitigate spaceflight health and performance risks. In this presentation, we will review details regarding the biospecimen and data archive to be generated by the NASA Omics Archive flight study. Data generated as part of this project will be archived in the NASA Life Sciences Portal (NLSP) and be made available for future hypothesis-driven research efforts or occupational surveillance through Institutional Review Board-approved data sharing and retrospective data requests submitted to the Life Sciences Data Archive (LSDA) team. We will also present results of a ground study performed to evaluate in-house procedures, new sample collection hardware, and vendor capabilities. The data repository generated and the samples to be archived by this study will enable future research efforts to assess an astronauts’ unique molecular and genetic profile with respect to individual spaceflight responses. Results of which will be instrumental in enabling precision health capabilities to better assess and mitigate spaceflight risks, detect disease states earlier, and actively monitor countermeasure treatments, ultimately improving clinical outcomes during future exploration class missions.

C. A. Theriot↗

NASA NTRSDate not supplied

Impact Outputs for A Representative Extended Duration Artemis Mission

BACKGROUND: As NASA and private industry begin preparation for long-duration spaceflight, quantifying the impact that potential human health and performance capabilities have on crew health outcomes is imperative for medical risk mitigation. NASA’s Informing Mission Planning via Analysis of Complex Tradespaces tool (IMPACT) applies Probabilistic Risk Assessment (PRA) methodology to estimate these outcomes. OVERVIEW: As NASA prepares to return to the Moon, medical system planning has already begun for extended Artemis missions, which will see humans spending months at a time in cis-lunar space and on the surface of the Moon. The Long Duration Lunar Orbital and Lunar Surface (LDLOLS) design reference mission (DRM) lasts 9 months, including 3 months on the lunar surface, and involves 2 male and 2 female crewmembers. LDLOLS assumes no extravehicular activities (EVAs) in orbit, but, while on the lunar surface, involves 2-4 EVAs/month in a pressurized rover and 2-4 EVAs/month in an unpressurized rover or on foot. This DRM assumes a physician level Crew Medical Officer with commensurate knowledge, skills, and abilities. The IMPACT tool was utilized to estimate in-flight medical risk for this mission. More specifically, 100,000 simulations of this DRM were modeled, and overall estimates for loss of crew life (LOCL), need for evacuation (RTDC; return to definitive care), and crew task time lost (TTL; a measure of disability) were calculated. A recommended medical capability set, with appropriate mass and volume constraints, was also generated. DISCUSSION: This abstract reviews the IMPACT-derived risk for these mission outcomes with and without treatment, a macroscopic look at the total mass and volume necessary for full diagnostic and treatment capability, and how these change with input mission parameters.

J G Steller↗

NASA NTRSDate not supplied

Quantifying the Sensitivity of Condition Incidence Parameters in the Evidence Library

One approach to quantifying spaceflight risk at NASA makes use event driven probabilistic techniques. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is such a tool that estimates medical risk metrics via simulation and enables optimization of medical resources subject to mission constraints [1]. Previous analyses have informed medical set composition, exercise countermeasures, and water intake, where each analysis quantifies the risk associated with proposed variations in system design. As future mission profiles extend beyond Low-Earth Orbit (LEO) and lengthen in duration, understanding these risks and contributing factors is critical. MEDPRAT employs Monte Carlo sampling techniques to simulate missions and track the occurrence of medical events. These events follow fault-tree-like progressions through levels of severity and mitigation via medical treatment to many possible outcomes and these are reported throughout the mission. Making this possible, are the medical databases that contain evidence gathered by the Human Research Program (HRP). Quantifying the impact of uncertainty or variability in the input data is an important step in evaluating the credibility of modeling and simulation results. In this work, we investigate the sensitivity of medical risk metrics with respect to the condition incidence parameters within the Evidence Library (EL) [2] as the medical database input for MEDPRAT. The medical conditions, contained in the EL, are equipped with incidence rates that describe the likelihood that the condition will occur. These incidence rates reflect historical spaceflight data or when appropriate, terrestrial data. In this presentation, we will explore how uncertainty in these rates propagate to the medical risk described by MEDPRAT. These results identify the conditions and parameters with the largest contribution to medical risks.

Ian Lim↗

NASA NTRS2015

Integrated Medical Model (IMM) 4.0 Enhanced Functionalities

The Integrated Medical Model is a probabilistic simulation model that uses input data on 100 medical conditions to simulate expected medical events, the resources required to treat, and the resulting impact to the mission for specific crew and mission characteristics. The newest development version of IMM, IMM v4.0, adds capabilities that remove some of the conservative assumptions that underlie the current operational version, IMM v3. While IMM v3 provides the framework to simulate whether a medical event occurred, IMMv4 also simulates when the event occurred during a mission timeline. This allows for more accurate estimation of mission time lost and resource utilization. In addition to the mission timeline, IMMv4.0 features two enhancements that address IMM v3 assumptions regarding medical event treatment. Medical events in IMMv3 are assigned the untreated outcome if any resource required to treat the event was unavailable. IMMv4 allows for partially treated outcomes that are proportional to the amount of required resources available, thus removing the dichotomous treatment assumption. An additional capability IMMv4 is to use an alternative medical resource when the primary resource assigned to the condition is depleted, more accurately reflecting the real-world system. The additional capabilities defining IMM v4.0the mission timeline, partial treatment, and alternate drug result in more realistic predicted mission outcomes. The primary model outcomes of IMM v4.0 for the ISS6 mission, including mission time lost, probability of evacuation, and probability of loss of crew life, are be compared to those produced by the current operational version of IMM to showcase enhanced prediction capabilities.

Spae Adaptation Syndrome↗

NASA NTRS1975

Bending stresses in spherically hollow ball bearing and fatigue experiments

Spherically hollow balls of 21.7, 50.0, and 56.5 percent mass reduction were operated in ball bearings and in a five-ball fatigue tester with differing outcomes. Available theoretical and experimental treatments of stresses in spherically hollow balls are reviewed and compared. Bending stresses are estimated for these spherically hollow balls to better understand the differences in ball bearing and fatigue test experience.

Nypan, L. J.↗

NASA NTRS1975

Bending stresses in spherically hollow ball bearing and fatigue experiments

Spherically hollow balls of 21.7, 50.0 and 56.5 per cent mass reduction have been operated in ball bearings and in a 5-ball fatigue tester with differing outcomes. Available theoretical and experimental treatments of stresses in spherically hollow balls are reviewed and compared. Bending stresses are estimated for these spherically hollow balls to better understand the differences in ball bearing and fatigue test experience.

Nypan, L. J.↗

NASA NTRS1977

Integrated study plan for space bioprocessing (phase 1)

Current economic evaluation and analytical techniques are applied to decision problems faced by the space bioprocessing program. NASA decision makers are enabled to choose candidate substances, after ranking them according to their potential economic benefit. The determination of appropriate evaluation techniques necessary to obtain measures of potential economic benefits which result from the pursuit of various space bioprocessing endeavors are focused upon. The treatment of each disease is impacted by a successful outcome of space bioprocessing and specify data and other input needs for each candidate substance.

Source record↗

NASA NTRS2014

Human Integration Design Processes (HIDP)

The purpose of the Human Integration Design Processes (HIDP) document is to provide human-systems integration design processes, including methodologies and best practices that NASA has used to meet human systems and human rating requirements for developing crewed spacecraft. HIDP content is framed around human-centered design methodologies and processes in support of human-system integration requirements and human rating. NASA-STD-3001, Space Flight Human-System Standard, is a two-volume set of National Aeronautics and Space Administration (NASA) Agency-level standards established by the Office of the Chief Health and Medical Officer, directed at minimizing health and performance risks for flight crews in human space flight programs. Volume 1 of NASA-STD-3001, Crew Health, sets standards for fitness for duty, space flight permissible exposure limits, permissible outcome limits, levels of medical care, medical diagnosis, intervention, treatment and care, and countermeasures. Volume 2 of NASASTD- 3001, Human Factors, Habitability, and Environmental Health, focuses on human physical and cognitive capabilities and limitations and defines standards for spacecraft (including orbiters, habitats, and suits), internal environments, facilities, payloads, and related equipment, hardware, and software with which the crew interfaces during space operations. The NASA Procedural Requirements (NPR) 8705.2B, Human-Rating Requirements for Space Systems, specifies the Agency's human-rating processes, procedures, and requirements. The HIDP was written to share NASA's knowledge of processes directed toward achieving human certification of a spacecraft through implementation of human-systems integration requirements. Although the HIDP speaks directly to implementation of NASA-STD-3001 and NPR 8705.2B requirements, the human-centered design, evaluation, and design processes described in this document can be applied to any set of human-systems requirements and are independent of reference missions. The HIDP is a reference document that is intended to be used during the development of crewed space systems and operations to guide human-systems development process activities.

Boyer, Jennifer↗

NASA NTRS2016

In-Flight Personalized Medication Management

Current medication selection for treatment of astronauts during spaceflight missions is primarily dictated by the task of efficiently treating the widest possible range of physiological conditions and illnesses with a limited set of medications. Dosage and recommendations on the combination of drugs are based on the assumption of genetically equal drug sensitivity and unchanged metabolism. To our knowledge, there was no pre-flight drug sensitivity testing on a genetic level for any of the previous manned NASA space missions. Although many of the common, binary drug-drug interactions are, most likely, already considered in the ISS Medical kit composition, multi-drug and multi-drug-gene factors are not incorporated in the medication selection or prescription. Furthermore, due to the physiological changes occurring in microgravity environments, astronauts might be susceptible to potential increased drug toxicity as a result of decreased clearance of numerous drugs. In particular, perturbation of CYP450 enzymes which contribute to the hepatic metabolism of the majority of drugs may have significant effects on therapeutic efficacy and increase treatment-related toxicity5. The genes encoding the CYP450 enzymes are highly variable in humans. Inheritable variations of CYP450 hepatic metabolizer enzymes and transport proteins play a crucial role in the inter-individual variability of drug efficiency and risks of adverse drug reactions5. Additionally, there are some reports that document changes in the levels of production of drug-metabolizing enzymes in microgravity. These data can be extrapolated to provide reasonable assumptions of decreased levels of expression for most CYP450 enzymes in human body during prolonged space travel. If the prescribed medication regiment is not fully effective or causes undesirable side effects, the ability of the astronauts to function and maintain peak performance levels during space flight could be seriously compromised. Therefore, technologies capable of predicting and managing medication side effects, interactions, and toxicity of drugs during spaceflight are needed. We propose to develop and customize for NASAs applications available on the market Personalized Prescribing System (PPS) that would provide a comprehensive, non-invasive solution for safer, targeted medication management for every crew member resulting in safer and more effective treatment and, consequently, better performance. PPS will function as both decision support and record-keeping tool for flight surgeons and astronauts in applying the recommended medications for situations arising in flight. The information on individual drug sensitivity will translate into personalized risk assessment for adverse drug reactions and treatment failures for each drug from the medication kit as well as predefined outcome of any combination of them. Dosage recommendations will also be made individually. The mobile app will facilitate ease of use by crew and medical professionals during training and flight missions.

Personalized Medication↗

NASA NTRS2017

Personalized Risk Assesment for Adverse Drug Reactions and Treatment Failures

As NASA and other space agencies prepare for future long-term space missions beyond the LEO, the cumulative impact of risk factors encountered in space increases substantially rising concerns about astronauts health. Application of on-board medications to mitigate clinical symptoms associated with certain medical conditions and illnesses is the first line of response to ensure sustainable health and performance of crew. Unfortunately, very limited research has been conducted to determine efficacy of the earth-based pharmaceuticals in a microgravity environment. In some instances, orally administered medications taken during flight were reported to be less effective than expected. Evaluation of series of experiments involving astronauts from shuttle flights shows notable individual variability to several pharmaceuticals during flight. These data provide reasonable assumption of perturbation in CYP450 enzymes during spaceflight, which contribute to the hepatic metabolism of the majority of drugs and therefore may have significant effects on therapeutic efficacy and increase treatment-related toxicity. The genes encoding the CYP450 enzymes are highly variable in humans. Inheritable variations of CYP450 hepatic metabolizer enzymes and transport proteins play a crucial role in the inter-individual variability of drug efficiency and risks of adverse drug reactions. Additionally, there are some reports that document changes in the levels of production of drug-metabolizing enzymes in microgravity. Therefore, in order to provide a safe and effective pharmaceutical treatment in space, medications selection should be based not only on the specific efficacy of medications but also on the individual drug sensitivity and flight-induced changes in metabolism of astronauts chosen for a particular mission. To our knowledge, there was no pre-flight drug sensitivity testing on a genetic level for any of the previous manned NASA space missions. Therefore, technologies capable of predicting and managing medication efficacy, side effects, and toxicity of drugs based on individual genetic variability of crew members are increasingly needed. In this report, we present results of testing the market available Personalized Prescribing System (PPS), a comprehensive, non-invasive solution for safer, targeted medication management for every crew member. Statistical accuracy and simplicity of non-invasive sample analysis demonstrate the feasibility of drug sensitivity assessment and record-keeping tool for flight surgeons and astronauts in applying the recommended medications for situations arising in flight. The information on individual drug sensitivity will translate into personalized risk assessment for adverse drug reactions and treatment failures for each drug from the medication kit as well as predefined outcome. This will address the HHC’s raised “Concern of Clinically Relevant Unpredicted Effects of Medication” as recently updated.

medications↗

NASA NTRS2011

Characterizing the Joint Effect of Diverse Test-Statistic Correlation Structures and Effect Size on False Discovery Rates in a Multiple-Comparison Study of Many Outcome Measures

In their 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report the results of a simulation assessing the robustness of their adaptive step-down procedure (GBS) for controlling the false discovery rate (FDR) when normally distributed test statistics are serially correlated. In this study we extend the investigation to the case of multiple comparisons involving correlated non-central t-statistics, in particular when several treatments or time periods are being compared to a control in a repeated-measures design with many dependent outcome measures. In addition, we consider several dependence structures other than serial correlation and illustrate how the FDR depends on the interaction between effect size and the type of correlation structure as indexed by Foerstner s distance metric from an identity. The relationship between the correlation matrix R of the original dependent variables and R~, the correlation matrix of associated t-statistics is also studied. In general R~ depends not only on R, but also on sample size and the signed effect sizes for the multiple comparisons.

Feiveson, Alan H.↗

NASA NTRS2018

Optimization of Picosecond Laser Parameters for Surface Treatment of Composites Using a Design of Experiments (DOE) Approach

Based on guidelines from the Federal Aviation Administration, research supported by the NASA Advanced Composites Project is investigating methods to improve process control for surface preparation and pre-bond surface characterization on aerospace composite structures. The overall goal is to identify high fidelity, rapid, and reproducible surface treatments and surface characterization methods to reduce the uncertainty associated with the bonding process. The desired outcome is a more reliable bonded airframe structure, and to reduce time to achieve certification. In this work, a design of experiments (DoE) approach was conducted to determine optimum laser ablation conditions using a pulsed laser source with a nominal pulse width of 10 picoseconds. The laser power, frequency, scan speed, and number of passes (1 or 2) were varied within the laser system operating boundaries. Aerospace structural carbon fiber reinforced composites (Torayca® 3900-2/T800H) were laser treated, then characterized for contamination, and finally bonded for mechanical testing. Pre-bond characterization included water contact angle (WCA) using a handheld device, ablation depth measurement using scanning electron microscopy (SEM), and silicone contamination measurement using laser induced breakdown spectroscopy (LIBS). In order to accommodate the large number of specimens in the DoE, a rapid-screening, double cantilever beam (DCB) test specimen configuration was devised based on modifications to ASTM D5528. Specimens were tested to assess the failure modes observed under the various laser surface treatment parameters. The models obtained from this DoE indicated that results were most sensitive to variation in the average laser power. Excellent bond performance was observed with nearly 100% cohesive failure for a wide range of laser parameters. Below about 200 mW, adhesive failure was observed because contamination was left on the surface. For laser powers greater than about 600 mW, large amounts of fiber were exposed, and the failure mode was predominately fiber tear.

Palmieri, Frank L.↗

NASA NTRSDate not supplied

MEDPRAT Treatment Clusters: Improving Representation of Mission Medical Risk

INTRODUCTION The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) implements a computational model that aims to quantify spaceflight medical risk by utilizing probabilistic techniques to simulate critical event incidence and outcomes over thousands of simulated mission trials. The goal of MEDPRAT is to characterize mission medical risk and provide insight into medical resource utilization. In order to analyze the medical resource space, treatment must be mapped from each simulated condition, and resources consumed as a result of this treatment must be tracked throughout the course of the mission. A new MEDPRAT feature, ‘treatment clusters’, provide a more sophisticated method of defining the structure and interaction between resources, more closely mimicking the way treatment is carried out clinically. METHODS Treatment clusters expand on the two existing treatment groupings (combination and alternate) adding a new grouping: bundled treatment. Treatment clusters may be combined to any depth, giving users the ability to specify complex treatment trees whose behavior is governed by several user-specified parameters. This approach emphasizes reusability, as treatment clusters, once defined, can be used to create more complex treatment trees or applied to many conditions. By configuring parameters for contribution, efficacy, necessity, primacy, and equivalence, resource relationships and dependencies can be more accurately represented, thereby allowing users to build capabilities with desired treatment properties, for example an intravenous capability for conditions such as anaphylaxis, acute radiation syndrome, etc. MEDPRAT v1.0 remains backward compatible with existing treatment structures, giving users the ability to define new treatment clusters as evidence becomes available, without having to recode their existing treatment databases. In addition to facilitating the representation of more complex treatment options, by pairing treatment clusters with the internal optimization routine, the MEDPRAT set selector, medical resources can be identified as organized in bundles, where appropriate, so that optimized resource sets include groups of highly-dependent resources only when all resources of the group are together. For example, it would be wasteful to include ultrasound gel but not an ultrasound machine, since the gel provides no benefit as a treatment without the ultrasound machine. With treatment clusters, the user may require that both resources are available to provide any benefit as treatment, so that if one resource is optimized out of the set, the other resource will be optimized out as well. RESULTS AND CONCLUSIONS We will report on MEDPRAT treatment clusters used in a bundling study under the IMPACT project of the ExMC element. We will discuss an example of a complex treatment tree. Through the implementation of this feature MEDPRAT enables treatment to be defined and applied in a way that is more representative of the real world, providing more accurate insight into mission medical risk and the medical resource space.

Lawrence Leinweber↗

NASA NTRS2017

Picosecond Pulsed Laser Ablation for the Surface Preparation of Epoxy Composites

As part of a technical challenge under the Advanced Composites Program, methods for improving pre-bond process control for aerospace composite surface treatments and inspections, in conjunction with Federal Aviation Administration guidelines, are under investigation. The overall goal is to demonstrate high fidelity, rapid and reproducible surface treatment and surface characterization methods to reduce uncertainty associated with the bonding process. The desired outcomes are reliable bonded airframe structure, and reduced timeline to certification. In this work, laser ablation was conducted using a q-switched Nd:YVO4 laser capable of nominal pulse durations of 8 picoseconds (ps). Aerospace structural carbon fiber reinforced composites with an epoxy resin matrix were laser treated, characterized, processed into bonded assemblies and mechanically tested. The characterization of ablated surfaces were conducted using scanning electron microscopy (SEM), water contact angle (WCA) goniometry, micro laser induced breakdown spectroscopy (uLIBS), and electron spin resonance (ESR). The bond performance was assessed using a double cantilever beam (DCB) test with an epoxy adhesive. The surface characteristics and bond performance obtained from picosecond ablated carbon fiber reinforced plastics (CFRPs) are presented herein.

Palmieri, Frank↗