Users can engage in rapid trade studies in geometry, structural layout
and material systems. MSC Apex is easy to use and learn, providing
an immersive user interface that’s fun with a game-like experience.
◗ MSC Software, www.mscsoftware.com
A Virtual Solution to Improving Energy Plant
Operations
EYESIM v2.3
Immersive Real-Time Virtual Reality Software for
Improving Energy
Plant Operations
and Safety, developed by the National
Energy Technology
Laboratory,
Schneider Electric and West Virginia Univ., is a comprehensive software
solution that provides a continuous, realistic view of commer-cial-scale energy plant operations by combining a high-performance,
immersive 3-D virtual reality engine with a high-fidelity, real-time,
dynamic plant simulator. EYESIM recreates the look-and-feel and
sounds of an actual operating plant. By enabling hands-on interaction with process equipment, EYESIM enables industry users to
optimize plant operations, control and maintenance, as well as safety
procedures for process malfunctions and abnormal situations. To
provide better process understanding, the EYESIM product also
offers augmented virtual reality that enables users to open and view
the internals of plant equipment during operation.
◗ National Energy Technology Laboratory, www.netl.doe.gov
Assessing Computational Behavior
Malware attacks are a global problem. Virtually all software contains
behavior unknown to its developers and users, and adversaries work
to exploit its unknown behavior. Oak Ridge National Laboratory’s
Hyperion: Automated Behavior Computation for Compiled Software is a semantics-based technology that computes software and
malware behavior
with mathematical precision at
machine speeds to
help deny adversaries access to the
nation’s computer
systems. Hyperion provides two
unique capabilities.
First, it automatically calculates
what an unknown program does under all possible inputs, without
execution or examining source code. Second, the Hyperion Behavior
Specification Units (BSUs) can capture, share and re-use malware
analyst expertise in identifying and detecting malicious behavior. This
leveraging of malware expertise multiplies the effectiveness of scarce
resources and gives defenders a powerful weapon.
Oak Ridge National Laboratory, www.ornl.gov
Advanced Reasoning Software
The amount of data streaming from cyber security appliances and
logs is staggering. The number of raw data points is best measured
in the millions of events per day, even for modestly sized institutions. Security analysts are trained to seek out and identify patterns
that represent cyber threats hidden inside the massive data streams.
Unfortunately, the velocity and volume of the streams are such that
even large teams of analysts are typically forced into forensic mode,
analyzing the data well after a compromise has occurred. Pacific
Northwest National Laboratory and Champion Technology Co.
Inc.’s CHAMPION (Columnar Hierarchical Auto-associative
Memory Processing in Ontological Networks) advanced reasoning
software system revolutionizes the detection of cyber threats. Behav-ior-based
patterns are
derived by
combining
subject matter
expertise and
knowledge
of analysts
with company-specific
historical
data, which
allows security analysts to
detect threats
in near-real-time. Domain- and company-specific data programmed
into the system for each specific user company makes the system
domain agnostic.
◗ Pacific Northwest National Laboratory, www.pnnl.gov
Predicting Power Needs
Pacific Northwest National Laboratory (PNNL)’s Power Model
Integrator evaluates different power forecasting models and determines how to best combine those models to make a single forecast
that more accurately predicts power needs. This enables energy managers to better estimate energy demands up to 4 hrs in advance. More
accurate energy forecasts help utilities and other power organizations
reduce the amount of
excess power generated
and also decrease the
need to suddenly buy
emergency power from
a broker at more than
four times the normal
price. The Power Model
Integrator also reduces
energy’s carbon footprint, as sudden energy
needs are usually met
with inefficient turbines
that make power quickly, but create more pollution in the process. The
Power Model Integrator uses PNNL-developed algorithms to assess up
to 35 different energy forecasting models and determine which models
