Evaluating methane storage targets: from powder samples to onboard storage systems

The development of a viable adsorbed natural gas onboard fuel system involves synthesizing materials that meet specific storage target requirements. We assess the impact on natural gas storage due to intermediate processes involved in taking a laboratory powder sample to an onboard packed or adsorbent bed module. We illustrate that reporting the V/V (volume of gas/volume of container) capacities based on powder adsorption data without accounting for losses due to pelletization and bed porosity, grossly overestimates the working storage capacity for a given material. Using data typically found for adsorbent materials that are carbon and MOF based materials, we show that in order to meet the Department of Energy targets of 180 V/V (equivalent STP) loading at 3.5 MPa and 298 K at the onboard packed bed level, the volumetric capacity of the pelletized sample should be at least 245 V/V and the corresponding gravimetric loading varies from 0.175 to 0.38 kg/kg for pellet densities ranging from 461.5 to 1,000 . With recent revision of the DOE target to 263 V/V at the onboard packed bed level, the volumetric loadings for the pelletized sample should be about 373 V/V.

Explicit Construction of Optimal Exact Regenerating Codes for Distributed Storage

Erasure coding techniques are used to increase the reliability of distributed storage systems while minimizing storage overhead. Also of interest is minimization of the bandwidth required to repair the system following a node failure. In a recent paper, Wu et al. characterize the tradeoff between the repair bandwidth and the amount of data stored per node. They also prove the existence of regenerating codes that achieve this tradeoff. In this paper, we introduce Exact Regenerating Codes, which are regenerating codes possessing the additional property of being able to duplicate the data stored at a failed node. Such codes require low processing and communication overheads, making the system practical and easy to maintain. Explicit construction of exact regenerating codes is provided for the minimum bandwidth point on the storage-repair bandwidth tradeoff, relevant to distributed-mail-server applications. A sub-space based approach is provided and shown to yield necessary and sufficient conditions on a linear code to possess the exact regeneration property as well as prove the uniqueness of our construction. Also included in the paper, is an explicit construction of regenerating codes for the minimum storage point for parameters relevant to storage in peer-to-peer systems. This construction supports a variable number of nodes and can handle multiple, simultaneous node failures. All constructions given in the paper are of low complexity, requiring low field size in particular.

Regenerating Codes for Distributed Storage Networks

In a storage system where individual storage nodes are prone to failure, the redundant storage of data in a distributed manner across multiple nodes is a must to ensure reliability. Reed-Solomon codes possess the reconstruction property under which the stored data can be recovered by connecting to any k of the n nodes in the network across which data is dispersed. This property can be shown to lead to vastly improved network reliability over simple replication schemes. Also of interest in such storage systems is the minimization of the repair bandwidth, i.e., the amount of data needed to be downloaded from the network in order to repair a single failed node. Reed-Solomon codes perform poorly here as they require the entire data to be downloaded. Regenerating codes are a new class of codes which minimize the repair bandwidth while retaining the reconstruction property. This paper provides an overview of regenerating codes including a discussion on the explicit construction of optimum codes.

First principles calculations of H-storage in sorption materials

A review of various contributions of first principles calculations in the area of hydrogen storage, particularly for the carbon-based sorption materials, is presented. Carbon-based sorption materials are considered as promising hydrogen storage media due to their light weight and large surface area. Depending upon the hybridization state of carbon, these materials can bind the hydrogen via various mechanisms, including physisorption, Kubas and chemical bonding. While attractive binding energy range of Kubas bonding has led to design of several promising storage systems, in reality the experiments remain very few due to materials design challenges that are yet to be overcome. Finally, we will discuss the spillover process, which deals with the catalytic chemisorption of hydrogen, and arguably is the most promising approach for reversibly storing hydrogen under ambient conditions.

New insights into designing metallacarborane based room temperature hydrogen storage media

Metallacarboranes are promising towards realizing room temperature hydrogen storage media because of the presence of both transition metal and carbon atoms. In metallacarborane clusters, the transition metal adsorbs hydrogen molecules and carbon can link these clusters to form metal organic framework, which can serve as a complete storage medium. Using first principles density functional calculations, we chalk out the underlying principles of designing an efficient metallacarborane based hydrogen storage media. The storage capacity of hydrogen depends upon the number of available transition metal d-orbitals, number of carbons, and dopant atoms in the cluster. These factors control the amount of charge transfer from metal to the cluster, thereby affecting the number of adsorbed hydrogen molecules. This correlation between the charge transfer and storage capacity is general in nature, and can be applied to designing efficient hydrogen storage systems. Following this strategy, a search for the best metallacarborane was carried out in which Sc based monocarborane was found to be the most promising H-2 sorbent material with a 9 wt.% of reversible storage at ambient pressure and temperature. (C) 2013 AIP Publishing LLC.

Regenerating codes for errors and erasures in distributed storage

Regenerating codes are a class of codes proposed for providing reliability of data and efficient repair of failed nodes in distributed storage systems. In this paper, we address the fundamental problem of handling errors and erasures at the nodes or links, during the data-reconstruction and node-repair operations. We provide explicit regenerating codes that are resilient to errors and erasures, and show that these codes are optimal with respect to storage and bandwidth requirements. As a special case, we also establish the capacity of a class of distributed storage systems in the presence of malicious adversaries. While our code constructions are based on previously constructed Product-Matrix codes, we also provide necessary and sufficient conditions for introducing resilience in any regenerating code.

Hydrogen energy future with formic acid: a renewable chemical hydrogen storage system

Formic acid, the simplest carboxylic acid, is found in nature or can be easily synthesized in the laboratory (major by-product of some second generation biorefinery processes); it is also an important chemical due to its myriad applications in pharmaceuticals and industry. In recent years, formic acid has been used as an important fuel either without reformation (in direct formic acid fuel cells, DFAFCs) or with reformation (as a potential chemical hydrogen storage material). Owing to the better efficiency of DFAFCs compared to several other PEMFCs and reversible hydrogen storage systems, formic acid could serve as one of the better fuels for portable devices, vehicles and other energy-related applications in the future. This perspective is focused on recent developments in the use of formic acid as a reversible source for hydrogen storage. Recent developments in this direction will likely give access to a variety of low-cost and highly efficient rechargeable hydrogen fuel cells within the next few years by the use of suitable homogeneous metal complex/heterogeneous metal nanoparticle-based catalysts under ambient reaction conditions. The production of formic acid from atmospheric CO2 (a greenhouse gas) will decrease the CO2 content and may be helpful in reducing global warming.

Discovery of Application Workloads from Network File Traces

An understanding of application I/O access patterns is useful in several situations. First, gaining insight into what applications are doing with their data at a semantic level helps in designing efficient storage systems. Second, it helps create benchmarks that mimic realistic application behavior closely. Third, it enables autonomic systems as the information obtained can be used to adapt the system in a closed loop.All these use cases require the ability to extract the application-level semantics of I/O operations. Methods such as modifying application code to associate I/O operations with semantic tags are intrusive. It is well known that network file system traces are an important source of information that can be obtained non-intrusively and analyzed either online or offline. These traces are a sequence of primitive file system operations and their parameters. Simple counting, statistical analysis or deterministic search techniques are inadequate for discovering application-level semantics in the general case, because of the inherent variation and noise in realistic traces.In this paper, we describe a trace analysis methodology based on Profile Hidden Markov Models. We show that the methodology has powerful discriminatory capabilities that enable it to recognize applications based on the patterns in the traces, and to mark out regions in a long trace that encapsulate sets of primitive operations that represent higher-level application actions. It is robust enough that it can work around discrepancies between training and target traces such as in length and interleaving with other operations. We demonstrate the feasibility of recognizing patterns based on a small sampling of the trace, enabling faster trace analysis. Preliminary experiments show that the method is capable of learning accurate profile models on live traces in an online setting. We present a detailed evaluation of this methodology in a UNIX environment using NFS traces of selected commonly used applications such as compilations as well as on industrial strength benchmarks such as TPC-C and Postmark, and discuss its capabilities and limitations in the context of the use cases mentioned above.

Experiments on thermal response of low aspect ratio packed beds at high Reynolds numbers with varying inflow temperature

An experimental study for transient temperature response of low aspect ratio packed beds at high Reynolds numbers for a free stream with varying inlet temperature is presented. The packed bed is used as a compact heat exchanger along with a solid propellant gas-generator, to generate room temperature gases for use in applications such as control actuation and air bottle pressurization. Packed beds of lengths similar to 200 mm and 300 mm were characterized for packing diameter based Reynolds numbers, Re-d ranging from 0.6 x 10(4) to 8.5 x 10(4). The solid packing used in the bed consisted of circle divide 9.5 mm and circle divide 5 mm steel spheres with suitable arrangements to eliminate flow entrance and exit effects. The ratios of packed bed diameter to packing diameter for 9.5 mm and 5 mm sphere packing were similar to 9.5 and 18 respectively, with the average packed bed porosities around 0.4. Gas temperatures were measured at the entry, exit and at three axial locations along centre-line in the packed beds. The solid packing temperature was measured at three axial locations in the packed bed. An average Nusselt number correlation of the form Nu(d) = 3.91Re(d)(05) for Re-d range of 10(4) is proposed. For engineering applications of packed beds such as pebble bed heaters, thermal storage systems, and compact heat exchangers a simple procedure is suggested for calculating unsteady gas temperature at packed bed exit for packing Biot number Bi-d < 0.1. (C) 2012 Elsevier Inc. All rights reserved.

What mainly controls recession flows in river basins?

The ubiquity of the power law relationship between dQ/dt and Q for recession periods (-dQ/dt kQ(alpha); Q being discharge at the basin outlet at time t) clearly hints at the existence of a dominant recession flow process that is common to all real basins. It is commonly assumed that a basin, during recession events, functions as a single phreatic aquifer resting on a impermeable horizontal bed or the Dupuit-Boussinesq (DB) aquifer, and with time different aquifer geometric conditions arise that give different values of alpha and k. The recently proposed alternative model, geomorphological recession flow model, however, suggests that recession flows are controlled primarily by the dynamics of the active drainage network (ADN). In this study we use data for several basins and compare the above two contrasting recession flow models in order to understand which of the above two factors dominates during recession periods in steep basins. Particularly, we do the comparison by selecting three key recession flow properties: (1) power law exponent alpha, (2) dynamic dQ/dt-Q relationship (characterized by k) and (3) recession timescale (time period for which a recession event lasts). Our observations suggest that neither drainage from phreatic aquifers nor evapotranspiration significantly controls recession flows. Results show that the value of a and recession timescale are not modeled well by DB aquifer model. However, the above mentioned three recession curve properties can be captured satisfactorily by considering the dynamics of the ADN as described by geomorphological recession flow model, possibly indicating that the ADN represents not just phreatic aquifers but the organization of various sub-surface storage systems within the basin. (C) 2014 Elsevier Ltd. All rights reserved.

Rational molecular dynamics scheme for predicting optimum concentration loading of nano-additive in phase change materials

The present study deals with the diffusion and phase transition behaviour of paraffin reinforced with carbon nano-additives namely graphene oxide (GO) and surface functionalized single walled carbon nanotubes (SWCNT). Bulk disordered systems of paraffin hydrocarbons impregnated with carbon nano-additives have been generated in realistic equilibrium conformations for potential application as latent heat storage systems. Ab initio molecular dynamics(MD) in conjugation with COMPASS forcefield has been implemented using periodic boundary conditions. The proposed scheme allows determination of optimum nano-additive loading for improving thermo-physical properties through analysis of mass, thermal and transport properties; and assists in determination of composite behaviour and related performance from microscopic point of view. It was observed that nanocomposites containing 7.8% surface functionalised SWCNT and 55% GO loading corresponds to best latent heat storage system. The propounded methodology could serve as a by-pass route for economically taxing and iterative experimental procedures required to attain the optimum composition for best performance. The results also hint at the large unexplored potential of ab-initio classical MD techniques for predicting performance of new nanocomposites for potential phase change material applications. (C) 2015 Author(s).

Investigation Into Harmful Patterns Over Multitrack Shingled Magnetic Detection Using the Voronoi Model

Two-dimensional magnetic recording 2-D (TDMR) is a promising technology for next generation magnetic storage systems based on a systems-level framework involving sophisticated signal processing at the core. The TDMR channel suffers from severe jitter noise along with electronic noise that needs to be mitigated during signal detection and recovery. Recently, we developed noise prediction-based techniques coupled with advanced signal detectors to work with these systems. However, it is important to understand the role of harmful patterns that can be avoided during the encoding process. In this paper, we investigate the Voronoi-based media model to study the harmful patterns over multitrack shingled recording systems. Through realistic quasi-micromagnetic simulation studies, we identify 2-D data patterns that contribute to high media noise. We look into the generic Voronoi model and present our analysis on multitrack detection with constrained coded data. We show that the 2-D constraints imposed on input patterns result in an order of magnitude improvement in the bit-error rate for the TDMR systems. The use of constrained codes can reduce the complexity of 2-D intersymbol interference (ISI) signal detection, since the lesser 2-D ISI span can be accommodated at the cost of a nominal code rate loss. However, a system must be designed carefully so that the rate loss incurred by a 2-D constraint does not offset the detector performance gain due to more distinguishable readback signals.

Access path query language for relational database systems

Database management systems offer a very reliable and attractive data organization for fast and economical information storage and processing for diverse applications. It is much more important that the information should be easily accessible to users with varied backgrounds, professional as well as casual, through a suitable data sublanguage. The language adopted here (APPLE) is one such language for relational database systems and is completely nonprocedural and well suited to users with minimum or no programming background. This is supported by an access path model which permits the user to formulate completely nonprocedural queries expressed solely in terms of attribute names. The data description language (DDL) and data manipulation language (DML) features of APPLE are also discussed. The underlying relational database has been implemented with the help of the DATATRIEVE-11 utility for record and domain definition which is available on the PDP-11/35. The package is coded in Pascal and MACRO-11. Further, most of the limitations of the DATATRIEVE-11 utility have been eliminated in the interface package.

Effect of Storage Temperatures on the Mechanical Properties of the Composite Solid Propellants

Accelerated ageing studies for three composite propellant formulations, namely polystyrene (PS)/ ammonium perchlorate (AP), polymethylmethacrylate (PMMA)/AP and poly phenol formaldehyde (PPF)/AP have been carried out in the temperature range of 55-125°C. Measurements of the ultimate compression strength (Uc) and isothermal decomposition rate (TD rate) were monitored as a function of storage time and temperature. The change in Uc was found to be linearly dependent on the change in TD rate irrespective of the propellant systems. Analysis of the results further revealed that the cause of ageing for both Uc and burning rate (r) is the thermal decomposition of the propellant. The safe-life for the change in mechanical properties was found to be higher compared to the change in r for PS and PMMA based propellants.

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the �Single Network Adaptive Critic (SNAC)� is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.