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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Biologically Inspired Micro-Flight Research

Natural fliers demonstrate a diverse array of flight capabilities, many of which are poorly understood. NASA has established a research project to explore and exploit flight technologies inspired by biological systems. One part of this project focuses on dynamic modeling and control of micro aerial vehicles that incorporate flexible wing structures inspired by natural fliers such as insects, hummingbirds and bats. With a vast number of potential civil and military applications, micro aerial vehicles represent an emerging sector of the aerospace market. This paper describes an ongoing research activity in which mechanization and control concepts for biologically inspired micro aerial vehicles are being explored. Research activities focusing on a flexible fixed- wing micro aerial vehicle design and a flapping-based micro aerial vehicle concept are presented.

Raney, David L.↗
NASA NTRS2006

Towards Biological Inspiration in the Development of Complex Systems

Greater understanding of biology in modem times has enabled significant breakthroughs in improving healthcare, quality of life, and eliminating many diseases and congenital illnesses. Simultaneously there is a move towards emulating nature and copying many of the wonders uncovered in biology, resulting in "biologically inspired" systems. Significant results have been reported in a wide range of areas, with systems inspired by nature enabling exploration, communication, and advances that were never dreamed possible just a few years ago. We warn, that as in many other fields of endeavor, we should be inspired by nature and biology, not engage in mimicry. We describe some results of biological inspiration that augur promise in terms of improving the safety and security of systems, and in developing self-managing systems, that we hope will ultimately lead to self-governing systems.

Hinchey, Michael G.↗
NASA NTRS1994

Biologically-inspired hexapod robot design and simulation

The design and construction of a biologically-inspired hexapod robot is presented. A previously developed simulation is modified to include models of the DC drive motors, the motor driver circuits and their transmissions. The application of this simulation to the design and development of the robot is discussed. The mechanisms thought to be responsible for the leg coordination of the walking stick insect were previously applied to control the straight-line locomotion of a robot. We generalized these rules for a robot walking on a plane. This biologically-inspired control strategy is used to control the robot in simulation. Numerical results show that the general body motion and performance of the simulated robot is similar to that of the robot based on our preliminary experimental results.

Espenschied, Kenneth S.↗
NASA NTRS2009

Biologically Inspired Purification and Dispersion of SWCNTs

A biologically inspired method has been developed for (1) separating single-wall carbon nanotubes (SWCNTs) from other materials (principally, amorphous carbon and metal catalysts) in raw production batches and (2) dispersing the SWCNTs as individual particles (in contradistinction to ropes and bundles) in suspension, as required for a number of applications. Prior methods of purification and dispersal of SWCNTs involve, variously, harsh physical processes (e.g., sonication) or harsh chemical processes (e.g., acid reflux). These processes do not completely remove the undesired materials and do not disperse bundles and ropes into individual suspended SWCNTs. Moreover, these processes cut long SWCNTs into shorter pieces, yielding typical nanotube lengths between 150 and 250 nm. In contrast, the present method does not involve harsh physical or chemical processes. The method involves the use of biologically derived dispersal agents (BDDAs) in an aqueous solution that is mechanically homogenized (but not sonicated) and centrifuged. The dense solid material remaining after centrifugation is resuspended by vortexing in distilled water, yielding an aqueous suspension of individual, separated SWCNTs having lengths from about 10 to about 15 microns.

Feeback, Daniel L.↗
DOE OSTI2018

A biologically-inspired approach for adaptive control of advanced energy systems

Here in this article, a novel approach is proposed for integrating a Biologically-Inspired Optimal Control Strategy (BIOsingle bondCS) with an Artificial Neural Network (ANN)-based adaptive component for advanced energy systems applications. Specifically, BIOsingle bondCS employs gradient-based optimal control solvers in a biologically-inspired manner, following the rule of pursuit for ants, to simultaneously control multiple process outputs at their desired setpoints. Also, the ANN component captures the mismatch between the controller and the plant models by using a single-hidden-layer technique with online learning capabilities to augment the baseline BIOsingle bondCS control laws. The resulting approach is a unique combination of biomimetic control and data-driven methods that provides optimal solutions for dynamic systems. The applicability of the proposed framework is illustrated via an Integrated Gasification Combined Cycle (IGCC) process with carbon capture as an advanced energy system example. In particular, a multivariable control structure associated with a subsystem of the IGCC plant simulation in DYNSIM® is addressed. The proposed control laws are derived in MATLAB®, while the plant models are built in DYNSIM®, and a previously developed MATLAB®-DYNSIM® link is employed for implementation purposes. The proposed integrated approach improves the overall performance of the process up to 85% in terms of reducing the output tracking error when compared to stand-alone BIOsingle bondCS and Proportional-Integral (PI) controller implementations, resulting in faster setpoint tracking. The proposed framework thus provides a promising alternative for advanced control of energy systems of the future.

42 ENGINEERING↗
NASA NTRS2003

Holarchical Systems and Emotional Holons : Biologically-Inspired System Designs for Control of Autonomous Aerial Vehicles

The BEES (Bio-inspired Engineering for Exploration Systems) for Mars project at NASA Ames Research Center has the goal of developing bio-inspired flight control strategies to enable aerial explorers for Mars scientific investigations. This paper presents a summary of our ongoing research into biologically inspired system designs for control of unmanned autonomous aerial vehicle communities for Mars exploration. First, we present cooperative design considerations for robotic explorers based on the holarchical nature of biological systems and communities. Second, an outline of an architecture for cognitive decision making and control of individual robotic explorers is presented, modeled after the emotional nervous system of cognitive biological systems. Keywords: Holarchy, Biologically Inspired, Emotional UAV Flight Control

Ippolito, Corey↗
DOE OSTI2019

Performance of biologically inspired algorithms tuned on TiO 2 nanoparticle benchmark system

Biologically inspired optimization algorithms (BIOA), such as particle swarm optimization (PSO) and differential evolution (DE), are often applied to a specific problem with the tacit assumptions that each algorithm will have a unique set of “ideal” tuning parameters that provide “best” performance, and that, once tuned, two different optimization algorithms ought to exhibit distinct performance. This work tests those assumptions by systematically comparing PSO and DE applied to identify stable and metastable configurations of a benchmark system, a titania dimer Ti 2 O 4 , whose energy is described by a modified Matsui-Akaogi pairwise potential. The hypotheses (H) are formally expressed as: (H1) for both PSO and DE there exists a unique, optimal set of tuning parameters that maximize its performance on a given problem; (H2) when running two different BIOAs, one algorithm must demonstrate superior performance over the other. By identifying and studying an approximate Pareto-optimal set of tuning parameters for DE and PSO, H1 is shown to be strictly false for DE, and tentatively false for PSO, while H2 is shown to be false with respect to certain statistics. Here, we further investigate the correlations between key tuning parameters and algorithm performance. Our conclusion may be implemented to further optimize and develop BIOAs applied to materials systems.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Biologically-Inspired Concepts for Autonomic Self-Protection in Multiagent Systems

Biologically-inspired autonomous and autonomic systems (AAS) are essentially concerned with creating self-directed and self-managing systems based on metaphors &om nature and the human body, such as the autonomic nervous system. Agent technologies have been identified as a key enabler for engineering autonomy and autonomicity in systems, both in terms of retrofitting into legacy systems and in designing new systems. Handing over responsibility to systems themselves raises concerns for humans with regard to safety and security. This paper reports on the continued investigation into a strand of research on how to engineer self-protection mechanisms into systems to assist in encouraging confidence regarding security when utilizing autonomy and autonomicity. This includes utilizing the apoptosis and quiescence metaphors to potentially provide a self-destruct or self-sleep signal between autonomic agents when needed, and an ALice signal to facilitate self-identification and self-certification between anonymous autonomous agents and systems.

Sterritt, Roy↗
NASA NTRS2006

The 'Biologically-Inspired Computing' Column

The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.

Hinchey, Mike↗
DOE OSTI2018

Biologically inspired approaches for biosurveillance anomaly detection and data fusion

This study developed and tested biologically inspired computational methods to detect anomalous signals in data streams that could indicate a pending outbreak or bio-weapon attack. Current large-scale biosurveillance systems are plagued by two principal deficiencies: (1) timely detection of disease-indicating signals in noisy data and (2) anomaly detection across multiple channels. Anomaly detectors and data fusion components modeled after human immune system processes were tested against a variety of natural and synthetic surveillance datasets. A pilot scale immune-system-based biosurveillance system performed at least as well as traditional statistical anomaly detection data fusion approaches. Machine learning approaches leveraging Deep Learning recurrent neural networks were developed and applied to challenging unstructured and multimodal health surveillance data. Within the limits imposed of data availability, both immune systems and deep learning methods were found to improve anomaly detection and data fusion performance for particularly challenging data subsets.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

Biologically inspired intelligent robotics

This paper will review the state of the art and challenges to biologically-inspired technologies and the role that EAP is expected to play as the technology evolves.

robotics EAP artificial muscles biomimetics↗
NASA NTRSDate not supplied

Design and Testing of the BionicWingSat in a Zero-g Flight Campaign - A 2U-CubeSat with Deployable, Biologically-Inspired Wings

In this paper, recent developments in the design, manufacturing, and testing of a novel deployable structure with several potential applications in space will be described. Through a cooperative effort of the German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA), a biologically inspired structurally integrated membrane featuring distributed functional elements has been developed and tested in a 2U CubeSat called BionicWingSat. Such a membrane structure could be useful for several applications in which a relatively flat area is desirable such as solar sails, drag sails, or solar shades. For SmallSats and CubeSats, the design proposed also has the desirable property of being self-deploying without the need for powered deployment mechanisms. Building on previous work inspired by the wings of earwigs, the research presented in this paper includes structural design of self-deploying hinges, a survey of various advanced additive layer manufacturing (ALM) methods for making hinges, mechanical characterization of the hinges, and finite element analysis (FEA) of the hinges. In this work, the conflicting goals of maximizing deployed structural stiffness, maximizing deployed area, maximizing stowed packaging efficiency, and maximizing resistance to creep when stowed must be considered. The resulting design concept is a gossamer structure that cannot support its own weight in gravity. For this reason, a focus in this paper is on a parabolic flight test campaign in which 24 fully integrated wings on two BionicWingSats were tested in a microgravity environment. From this test campaign, several lessons were learned regarding the wing design and procedures for carrying out microgravity tests of this manner.

CubeSat↗
NASA NTRSDate not supplied

Design and Testing of the BionicWingSat in a Zero-g Flight Campaign - A 2U-CubeSat with Deployable, Biologically-Inspired Wings

In this paper, recent developments in the design, manufacturing, and testing of a novel deployable structure with several potential applications in space will be described. Through a cooperative effort of the German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA), a biologically inspired structurally integrated membrane featuring distributed functional elements has been developed and tested in a 2U CubeSat called BionicWingSat. Such a membrane structure could be useful for several applications in which a relatively flat area is desirable such as solar sails, drag sails, or solar shades. For SmallSats and CubeSats, the design proposed also has the desirable property of being self-deploying without the need for powered deployment mechanisms. Building on previous work inspired by the wings of earwigs, the research presented in this paper includes structural design of self-deploying hinges, a survey of various advanced additive layer manufacturing (ALM) methods for making hinges, mechanical characterization of the hinges, and finite element analysis (FEA) of the hinges. In this work, the conflicting goals of maximizing deployed structural stiffness, maximizing deployed area, maximizing stowed packaging efficiency, and maximizing resistance to creep when stowed must be considered. The resulting design concept is a gossamer structure that cannot support its own weight in gravity. For this reason, a focus in this paper is on a parabolic flight test campaign in which 24 fully integrated wings on two BionicWingSats were tested in a microgravity environment. From this test campaign, several lessons were learned regarding the wing design and procedures for carrying out microgravity tests of this manner.

CubeSat↗
NASA NTRS1990

Identification of the connections in biologically inspired neural networks

We developed an identification method to find the strength of the connections between neurons from their behavior in small biologically-inspired artificial neural networks. That is, given the network external inputs and the temporal firing pattern of the neurons, we can calculate a solution for the strengths of the connections between neurons and the initial neuron activations if a solution exists. The method determines directly if there is a solution to a particular neural network problem. No training of the network is required. It should be noted that this is a first pass at the solution of a difficult problem. The neuron and network models chosen are related to biology but do not contain all of its complexities, some of which we hope to add to the model in future work. A variety of new results have been obtained. First, the method has been tailored to produce connection weight matrix solutions for networks with important features of biological neural (bioneural) networks. Second, a computationally efficient method of finding a robust central solution has been developed. This later method also enables us to find the most consistent solution in the presence of noisy data. Prospects of applying our method to identify bioneural network connections are exciting because such connections are almost impossible to measure in the laboratory. Knowledge of such connections would facilitate an understanding of bioneural networks and would allow the construction of the electronic counterparts of bioneural networks on very large scale integrated (VLSI) circuits.

Demuth, H.↗
NASA NTRS2006

Biologically-Inspired Concepts for Self-Management of Complexity

Inherent complexity in large-scale applications may be impossible to eliminate or even ameliorate despite a number of promising advances. In such cases, the complexity must be tolerated and managed. Such management may be beyond the abilities of humans, or require such overhead as to make management by humans unrealistic. A number of initiatives inspired by concepts in biology have arisen for self-management of complex systems. We present some ideas and techniques we have been experimenting with, inspired by lesser-known concepts in biology that show promise in protecting complex systems and represent a step towards self-management of complexity.

Sterritt, Roy↗
NASA NTRS2007

The "Biologically-Inspired Computing" Column

Self-managing systems, whether viewed from the perspective of Autonomic Computing, or from that of another initiative, offers a holistic vision for the development and evolution of biologically-inspired computer-based systems. It aims to bring new levels of automation and dependability to systems, while simultaneously hiding their complexity and reducing costs. A case can certainly be made that all computer-based systems should exhibit autonomic properties [6], and we envisage greater interest in, and uptake of, autonomic principles in future system development.

Hinchey, Mike↗