Template Tag Field Descriptions

Input Tag and Output Tag Field Descriptions

This topic describes the fields that can be viewed in the Input Tag and Output Tag grid.

ColumnDescription
ActionsIn this column, you can select to modify a tag, or you can select to delete a tag.

If the tag is configured to generate a calculated value, appears in this column. You can select to view the formula for the calculation.

NameThe name of the tag.
Calculated EstimateEstimate generated by a user defined expression rather than the reference data selection algorithm.
DescriptionThe description of the tag.
Actual HighThresholds used in rules to determine whether data is outside of expected limits.
Actual Low
Adaptation HighUpper and lower thresholds used to determine the range of data that can be adapted into models from runtime using the auto-adaptation algorithms.
Adaptation Low
Tag IDAutomatically generated unique ID for the tag. This value cannot be modified.
Measurement UnitsThe units of measure for the source data of the tag, such as degrees (C) or percentage (%). This is used only as an identifying label and is displayed on the y-axis when the tag is used in model training data charts.
Standard UnitsThe units of measurement for the source data for the tag.
Data TypeThe data format of the tag. The options are Float, Integer, Boolean, String, or Date. The data type cannot be changed once a tag is added and the analytic template is saved.
Tag TypeIf the tag is configured to generate a calculated value, appears in this column. You can select to view the formula for the calculation.
Decimal ScaleThe number of decimal places included in the tag readings. This value is inherited from templates imported from Classic SmartSignal Blueprint Center. It is not used in APM and cannot be modified.
Step High ThresholdThresholds used for step-change rules.
Step Low Threshold
NotesNotes about the tag.
Chart Y MinChart Y Min and Max values override default chart automatic scaling on the y-axis.

In other words, by default, analysis charts are automatically scaled on the y-axis based on tag reading values. For example, if you have a tag with reading values that range from 10 through 30, the bottom of the y-axis in the chart has a value of 10, and the top of the y-axis has a value of 30. If you prefer to see a chart that starts at 0 and ends at 50 in the y-axis, you can enter 0 in the Chart Y Min column and 50 in the Chart Y Max column.

Note: If you imported an analytic template from a SmartSignal Classic blueprint, if that blueprint had Chart Y Min and Max values, those values are maintained in APM.
Chart Y Max

Output Tag Field Descriptions

This topic describes the fields that can be viewed in the Output Tag grid.

ColumnDescription
ActionsIn this column, you can select to modify a tag, or you can select to delete a tag.

If the tag is configured to generate a calculated value, appears in this column. You can select to view the formula for the calculation.

NameThe name of the tag.
Calculated EstimateEstimate generated by a user defined expression rather than the reference data selection algorithm.
DescriptionThe description of the tag.
Actual HighThreshold used in rules to determine whether data is outside of expected limits.
Actual LowThreshold used in rules to determine whether data is outside of expected limits.
Adaptation HighUpper threshold used to determine the range of data that can be adapted into models from runtime using the auto-adaptation algorithms.
Adaptation LowLower threshold used to determine the range of data that can be adapted into models from runtime using the auto-adaptation algorithms.
Tag IDAutomatically generated unique ID for the tag. This value cannot be modified.
Measurement UnitsThe units of measure for the source data of the tag, such as degrees (C) or percentage (%). This is used only as an identifying label and is displayed on the y-axis when the tag is used in model training data charts.
Standard UnitsThe units of measurement for the source data for the tag.
Data TypeThe data format of the tag. The options are Float, Integer, Boolean, String, or Date. The data type cannot be changed once a tag is added and the analytic template is saved.
Tag TypeIf the tag is configured to generate a calculated value, appears in this column. You can select to view the formula for the calculation.
Decimal ScaleThe number of decimal places included in the tag readings. This value is inherited from templates imported from Classic SmartSignal Blueprint Center. It is not used in APM and cannot be modified.
Step High ThresholdThreshold used for step-change rules.
Step Low Threshold
NotesNotes about the tag.

Constant Tag Field Descriptions

This topic describes the fields that can be viewed in the Constant Tag grid.

Table 1. Analytic Level Constants
ColumnDescription
ActionsIn this column, you can select to modify a tag, or you can select to delete a tag.
NameThe name of the tag.
DescriptionThe description of the tag.
Data TypeThe data format for the tag. The options are Float, Integer, Boolean, String, or Date. Once a tag is added and the analytic template is saved, you cannot modify the data type.
Default ValueThe default value for the tag.
Note: For constant tags with a type of Date, no default value can be selected.
NotesNotes about the tag.
Table 2. Model Level Constants
ColumnDescription
ActionsIn this column, you can select to modify a tag, or you can select to delete a tag.
NameThe name of the tag.
ModeThe mode with which the tag is associated.
ModelThe model with which the tag is associated.
DescriptionThe description of the tag.
Data TypeThe data format for the tag. The options are Float, Integer, Boolean, String, or Date. Once a tag is added and the analytic template is saved, you cannot modify the data type.
Default ValueThe default value for the tag.
Note: For constant tags with a type of Date, no default value can be selected.
NotesNotes about the tag.

Modes Field Descriptions

This topic describes the fields that can be viewed in the Modes grid.

FieldPurpose
ActionsIn this column, you can select to modify a tag, or you can select to delete a tag.
NameThe name for the mode analytic template.
DescriptionThe description for this mode analytic template.
ExpressionThe expression used to define the mode condition.
Is ValidBoolean value used to determine the validity of the expression.
NotesThe notes for this mode analytic template.

Models Field Descriptions

This topic describes the fields that can be viewed in the Models grid.

FieldPurpose
ActionsIn this column, you can select to modify a tag, or you can select to delete a tag.
Display NameThe name of the model analytic template.
ModeThe mode with which the tag is associated.
DescriptionDescription of the model analytic template.
Estimate GeneratorA reference data selection algorithm used to generate estimated values. There are two types of estimate generators:
SBM
Similarity Based Model
VBM
Variable Similarity Based Model
Similarity OperatorOne of the following algorithms used for modeling:
SSCOP2
A similarity operator used during estimate generation. It is most useful for auto associative modeling. It tends to be a more fault tolerant than SSCOP3.
SSCOP3
An alternative similarity operator. It provides a smoother estimate of the response variables, and tends to perform better in inferential modeling cases. However, it is less fault tolerant than SSCOP2 which is why we often assume that the predictor (input) variables can be considered good. If it turns out not to be the case, spillover can occur in one or more of the response variables (inferred variables).
Enable VSGSpecifies whether or not virtual signal generation is enabled. If NaNs and/or outliers are encountered and the number of tags containing bad data is below the Maximum % of Bad Tags threshold, the system will fill in the missing or bad data for modeled tags with virtual signal data.
Max Percentage of Bad TagsThe percentage threshold above which the system inhibits virtual signal generation.
Variance Scale FactorA multiplier for the standard deviation of normal residual signals.
Residual Smoothing - Smoothing Algorithm
Moving Average
The simplest of the three smoothing algorithms. It is a moving window technique where the system averages the data within each window to produce the filtered sample for each window. Although simple and computationally efficient, there is an inherent delay in the response of the filter that is proportional to the window size. Also, the presence of a spike in the input data will affect the output signal for the length of the window size.
Spline
A real-time moving window technique that employs a cubic-spline fit to each of the individual sliding windows. The spline filter can produce a filtered signal with very little delay, but this is more computationally expensive. Also, a spike in the input data results in a shift in the output, but this effect will be short-lived compared to the moving average filter.
Olympic
This filter is very similar to the Moving Average filter, but the system does not use the maximum and minimum data samples for each window in the calculation of the average value. The resulting filter is very computationally efficient and effective at removing spikes. However, it suffers from the same response delay as the Moving Average filter.
Residual Smoothing - Window SizeThe total window (the number of data points or persistence) to use for smoothing.
Residual Smoothing - SplineA number between 0 and 1, where the value 0 causes the greatest smoothing and a value of 1 results in no smoothing (the output values equal the input values). A typical default value is 0.1.
State Matrix Creation - Down Sample AlgorithmOne of the following algorithms that is used when creating the state matrix:
Min Max
This algorithm finds where the maximum and minimum values for each tag occur and then uses those samples as the basis for the state matrix. If the same vector is identified from two different tags, the redundancy is eliminated. This method provides the minimum number of vectors in the training matrix.
Vector Ordering
This algorithm is the recommended choice. This algorithm identifies samples to include in the state matrix by spacing the magnitudes of each training snapshot. A training snapshot is a data sample containing a reading from each tag. If the same vector is identified from two different tags the redundancy is eliminated. The appropriate target number of observations in the state matrix is entered in the Target Vectors box. This method is useful for data that contains many states and is non-stationary (i.e., the mean of the tags varies over time).
Min Max Split
This method applies the MinMax algorithm to equal-sized sections of data. This method returns more data than the MinMax method, so you can use this method if the MinMax method does not return enough observations for model training. When this method is selected, the Reference Data Splits box appears.
Maximum VectorsThe maximum number of vectors to include in the state matrix. This option works with models that have auto adaptation. If the maximum vectors are larger than the target vectors, it will increase the size of the state matrix. For example, if the target vectors is set to 25 and the maximum vectors is set to 50, the first 25 times auto adaptation occurs, the state matrix will become larger, then it will stop increasing at 50. If the maximum vectors is smaller than the target vectors, this field will have no effect.
State Matrix Creation - Target VectorsThe number of vectors that will be targeted when the state matrix is created. Used when Vector Ordering is specified in the Downsample Algorithm box.
VBM - Fixed Size LocalD
Fixed
The VBM state matrix will contain exactly this many vectors.
Variable
The VBM state matrix will select a number of vectors between the minimum and maximum (below).
Similarity PercentileThreshold used to determine whether or not vectors are different enough from each other to both be considered for the VBM state matrix.
Redundancy Check TimeSpecifies when redundancy checks are to be executed (e.g., during runtime or setup of the model).
Reference Data SplitsThe number of sections to which the MinMax algorithm should be applied. Used when Min Max Split is specified in the Downsample Algorithm box.
NotesNotes about the model analytic template.
Created DateDate the model analytic template was created.
Last Changed DateDate the model analytic template was last modified.

Model Tags Field Descriptions

This topic describes the fields that can be viewed in the Model Tags grid.

ColumnDescription
ActionsIn this column, you can select to modify a tag, or you can select to delete a tag.
NameThe name of the tag.
Is In ModelIf selected, this analytic template tag will be included as part of the model blueprint. The collection of model-specific settings and data for this tag are collectively referred to as a model tag.
ModeThe mode with which the tag is associated.
ModelThe model with which the tag is associated.
Alarm TypeDefines the algorithm used to trigger residual indications.
None
Disables residual indications for the residual signal for the tag.
SPRT
This is a specialized decision algorithm called the Sequential Probability Ratio Test (SPRT). The system can apply it when the residuals are normally distributed and serially uncorrelated. The algorithm uses a statistical hypothesis testing technique to determine if the mean of the residual has shifted in the positive or negative direction.
Residual Threshold
This is the default value. It triggers a residual indication if the residual signal of the tag exceeds the value in the Positive Residual Threshold column or falls below the value in the Negative Residual Threshold column.
Smoothed Residual Threshold
Triggers a residual indication if the smoothed residual signal of the tag exceeds the value in the Residual + Threshold column or falls below the value in Residual - Threshold column. This method is used to remove spike data and noise from the residuals.
Is IndependentInferential models use an observation of measured signal values to generate one or more estimated signal values not present in the observation of measured signal values. When using this method, this field indicates whether the independent variables should represent all of the drivers for the dependent output variables.
Is DriverAny tags with this selected will be looked at to determine if a new operating state is occurring to trigger auto adaptation. At least one tag must be checked to enable auto-adaptation.
Residual VarianceUsed to set a custom value of residual variance for use by the SPRT algorithm.  If not set, each Asset will use the variance if the residual across its training data.  Do not change this setting without fully understanding what it does.
Negative Outlier ThresholdThreshold used for outlier rules.
Positive Outlier ThresholdThreshold used for outlier rules.
Negative Residual ThresholdThe maximum absolute value allowed for a negative residual (i.e., when the estimate is below the actual for a signal).  See details in the Alarm Type column.
Positive Residual ThresholdThe maximum absolute value allowed for a positive residual (i.e., when the estimate is above the actual for a signal).  See details in the Alarm Type column.
Negative SPRT SensitivityThe negative values for the sensitivity of the SPRT. This value is multiplied by the standard deviation of the residual, which in turn defines the amount of negative change in the residual mean that must occur to constitute an alarm.
Positive SPRT SensitivityThe positive values for the sensitivity of the SPRT.  This value is multiplied by the standard deviation of the residual, which in turn defines the amount of positive change in the residual mean that must occur to constitute an alarm.
Model Tag Display NameThe display name of the tag.
Data TypeThe data format for the tag. The options are Float, Integer, Boolean, String, or Date.
Tag TypeThe type of tag (i.e., Input, Output, or Constant).
DescriptionThe description of the tag.
Filter HighThe upper filtering threshold.  This field sets the upper threshold value for filtering of tag signals to remove data outside the normal operating range. Any tag data greater than this value is considered an outlier.  Outliers will be filtered out of training data.
Filter LowThe lower filtering threshold.  This field sets the lower threshold value for filtering of tag signals to remove data outside the normal operating range. Any tag data less than this value is considered an outlier.  Outliers will be filtered out of training data.
Flat Line NumberIf the data for this tag remains at the same level for more than this number of data points, the data will be considered to be flat lined, and will be filtered out of training data.
Spike SensitivityThe sensitivity of the spike detection algorithm used to detect spikes in tag signals.  A higher value will detect more spikes, but may also generate false positives.  Spike data will be filtered out of training data.  Do not change this setting without fully understanding what it does.
NotesThe notes for the tag.

Diagnostic Rules Field Descriptions

This topic describes the fields that can be viewed in the Diagnostic Rules grid.

FieldPurpose
ActionsIn this column, you can select to modify a tag, or you can select to delete a tag.
NameThe name for the diagnostic rule.
ExpressionThe expression used to define the mode condition.
Is ValidBoolean value used to determine the validity of the expression.
Startup Suppression Poll CyclesSpecifies the number of poll cycles the rule will be suppressed (that is, not evaluated) after the asset enters a new mode.
ActiveBoolean values that determines whether the tag is active or inactive.
DescriptionThe description for the diagnostic rule.
NotesThe notes for the diagnostic rule.

Tag Rules Field Descriptions

This topic describes the fields that can be viewed in the Tag Rules grid.

FieldPurpose
ActionsIn this column, you can select to modify a tag, or you can select to delete a tag.
Display NameDisplays the name of the rule. A green check mark displayed next to the name field indicates that the item is ready to be used. A yellow triangle indicates that the rule is not ready to be used. Hover over the yellow triangle to see which information is missing from the rule.
DescriptionA description for this rule.
MnemonicAbbreviation used to identify the rule to assist with references in diagnostics rules.
Suppression Poll CycleSpecifies the number of poll cycles the rule will be suppressed (that is, not evaluated) after the asset enters a new mode.
PriorityThe priority of the rule; affects display of advisories in the application.
MessageConfigures the message that will appear for the advisory. There are four options that can be displayed in the message: Source Tag, Description, Alias, and Asset.
ExpressionThe expression used to define the mode condition.
NotesNotes for this rule.

Input Tag UOM

This topic lists the UOM names that are currently supported by the SmartSignal Input Tag UOM conversion feature.

CategoryNameDescriptionAlias name in APM UOM
PressurePSIGPound-force per square inch gaugepsi g, psig, PSIG
PSIAPounds-force per square inch absolutepsi a, psia, psi, PSIA
inHgInches of mercuryin.Hg, inHgA, inHg a, inHg
mmHgMillimeters of mercurymm.Hg a, mmHg,
inH2OInches of waterin.H2O a, inH2O
ftH2OFeet of waterft.H2O a,ftH2O
BarUnits of pressurebar,bar a, Bar, BAR
PaPascalPa
KPaKilopascalsKPa
TorrUnits of pressureTorr
AtmAtmospheresatm
BarGBars gaugebarg, bar g, bar(g), BarG
mmH2OMillimeters of watermm.H2O, mm.H2O a, mmH2O
mBarMillibarmBar
MPaMegapascalMPa
hPaHectopascalhPa, HPA
daPaDekapascaldaPa
dPaDecipascaldPa
cPaCentipascalcPa
milliPa = 49,MillipascalmPa, milliPa
μPaMicropascaluPa
KilogramsPerSquareCentimeterAbsolutekg/cm^2 aKilogramsPerSquareCentimeterAbsolute, kg/cm2 a
KilogramsPerSquareCentimeterGaugekg/cm^2 gKilogramsPerSquareCentimeterGauge, kg/cm2 g
inHgGInches of mercury GaugeinHgG, in.Hg g
mmHgGMillimeters of mercury GaugemmHgG , mm.Hg g
inH2OGInches of water Gaugein.H2O g, inH2OG
ftH2OGFeet of water Gaugeft.H2O g, ftH2OG
mmH2OGMillimeters of water Gaugemm.H2O g, mmH2OG
mBarGMillibar GaugemBarG, mBarg, mBar g,mBarG
TemperatureCelsiusCelsiusCelsius, Deg C, deg C, DEG C
FahrenheitFahrenheitFahrenheit, Deg F, deg F, DEG F
KelvinKelvinKelvin
RankineRankineRankine
FrequencyRPMRevolutions per minuterpm, RPM
CPSCycles per secondcycles/sec, cycles/s, CPS
CPMCycles per minutecycles/min, CPM
SpeedFPMFeet per minuteft/min, FPM
MPMMeters per minutem/min, MPM
IPSInches per secondin/sec, in/s, IPS
MetersPerSecondm/secm/sec, m/s, MetersPerSecond
MillimetersPerSecondmm/secmm/sec, mm/s, MillimetersPerSecond
MicrometersPerSecondμm/secum/sec, um/s, MicrometersPerSecond
FeetPerSecondft/secft/sec, ft/s, FeetPerSecond
HertzHzHz, Hertz
FlowRateVolumeGPMGallons per minutegal/min, GPM
GPHGallons Per Hourgal/hr, GPH
CFMCubic feet per minuteft3/min, CFM
m3PerHourCubic meters per hourm3/hr, m3PerHour
LPSLiters per secondliter/sec, liter/s, LPS
LBMPerHourPounds mass per hourlbm/hr, LBMPerHour, lb/hr
kLBMPerHourKilo-pounds mass per hourklbm/hr, kLBMPerHour
kgPerHourKilograms per hourkg/hr, kgPerHour
kgPerSecondKilograms per secondkg/sec, kg/s, kgPerSecond
CFSCubic feet per secondft3/sec, ft3/s, CFS
CFHCubic feet per hourft3/hr, CFH
CFDCubic feet per dayft3/day, CFD
kCFMThousands of Cubic feet per minutek(ft3)/min, kCFM
kCFSThousands of Cubic feet per secondk(ft3)/sec, kCFS
kCFHThousands of Cubic feet per hourk(ft3)/hr , kCFH
kCFDThousands of Cubic feet per dayk(ft3)/day, kCFD
MCFMMillions of Cubic feet per minuteM(ft3)/min, MCFM
MCFSMillions of Cubic feet per secondM(ft3)/sec, M(ft3)/s, MCFS
MCFHMillions of Cubic feet per hourM(ft3)/hr, MCFH
MCFDMillions of Cubic feet per dayM(ft3)/day, MCFD
GPSGallons per secondgal/sec, gal/s, GPS
GPDGallons per daygal/day, GPD
m3PerSecondCubic meters per secondm3/sec, m3/s, m3PerSecond
m3PerMinuteCubic meters per minutem3/min, m3PerMinute
m3PerDayCubic meters per daym3/day, m3PerDay
LPMLiters per minuteliter/min, LPM
LPHLiters per hourliter/hr , LPH
LPDLiters per dayliter/day,LPD
ccPerSecondCubic centimeters per secondcm3/sec, cm3/s, ccPerSecond
ccPerMinuteCubic centimeters per minutecm3/min, ccPerMinute
ccPerHourCubic centimeters per hourcm3/hr, ccPerDay
ccPerDayCubic centimeters per daycm3/day, ccPerDay
FlowRateVolumein3PerSecondCubic inches per secondin3/sec, in3/s, in3PerSecond
in3PerMinuteCubic inches per minutein3/min, in3PerMinute
in3PerHourCubic inches per hourin3/hr, in3PerHour
in3PerDayCubic inches per dayin3/day, in3PerDay
FlowRateVolumeBBSBarrels (oil) per secondbbl/sec, bbl/s, BBS
BBMBarrels (oils) per minutebbl/min, BBM
BBHBarrels (oils) per hourbbl/hr, BBH
BBDBarrels (oils) per daybbl/day, BBD
kBBSThousands of Barrels (oil) per secondkbbl/sec, kbbl/s, kBBS
kBBMThousands of Barrels (oils) per minutekbbl/min, kBBM
kBBHThousands of Barrels (oils) per hourkbbl/hr, kBBH
kBBDThousands of Barrels (oils) per daykbbl/day, kBBD
MBBSMillions of Barrels (oil) per secondMbbl/sec, Mbbl/s, MBBS
MBBMMillions of Barrels (oils) per minuteMbbl/min, MBBM
MBBHMillions of Barrels (oils) per hourMbbl/hr, MBBH
MBBDMillions of Barrels (oils) per dayMbbl/day, MBBD
LBMPerSecondPounds mass per secondlbm/sec, lbm/s, LBMPerSecond, lb/s, lb/sec
LBMPerMinutePounds mass per minutelbm/min, LBMPerMinute, lb/min
LBMPerDayPounds mass per daylbm/day, LBMPerDay, lb/day
kLBMPerSecondKilo-pounds mass per secondklbm/sec, klbm/s, kLBMPerSecond
kLBMPerMinuteKilo-pounds mass per minuteklbm/min, kLBMPerMinute
kLBMPerDayKilo-pounds mass per dayklbm/day, kLBMPerDay
MLBMPerHourMega-Pounds mass per hourMlbm/hr, MLBMPerHour
MLBMPerSecondMega-Pounds mass per secondMlbm/sec, Mlbm/s, MLBMPerSecond
MLBMPerMinuteMega-Pounds mass per minuteMlbm/min, MLBMPerMinute
MLBMPerDayMega-Pounds mass per dayMlbm/day, MLBMPerDay
kgPerMinuteKilograms per minutekg/min, kgPerMinute
kgPerDayKilograms per daykg/day, kgPerDay
MetricTonPerSecondMetric Ton per secondMetric Ton/sec, MetricTonPerSecond
MetricTonPerMinuteMetric Ton per minuteMetric Ton/min, MetricTonPerMinute
MetricTonPerDayMetric Ton per dayMetric Ton/day, MetricTonPerDay
MetricTonPerHourMetric ton per hourMetric Ton/hr, MetricTonPerHour
FlowRateVolumeThousandsOfCubicMetersPerSecondk(m^3)/sk(m3)/sec, k(m3)/s, ThousandsOfCubicMetersPerSecond
ThousandsOfCubicMetersPerMinutek(m^3)/mk(m3)/min, ThousandsOfCubicMetersPerMinute
ThousandsOfCubicMetersPerHourk(m^3)/hk(m3)/hr, ThousandsOfCubicMetersPerHour
ThousandsOfCubicMetersPerDayk(m^3)/dk(m3)/day, ThousandsOfCubicMetersPerDay
MillionsOfCubicMetersPerSecondM(m^3)/sM(m3)/sec, MillionsOfCubicMetersPerSecond
MillionsOfCubicMetersPerMinuteM(m^3)/mM(m3)/min, MillionsOfCubicMetersPerMinute
MillionsOfCubicMetersPerHourM(m^3)/hM(m3)/hr, MillionsOfCubicMetersPerHour
MillionsOfCubicMetersPerDayM(m^3)/dM(m3)/day, MillionsOfCubicMetersPerDay
PowerHPHorsepower (International)hp, HP
WWattsW
MWMegawattsMW
kWKilowattskW
NmPerSecondNewton meters per secondN-m/sec, NmPerSecond
BTUPerHourBTU / Hourbtu/hour, BTUPerHour
MBTUPerHRMillion BTU / hourMbtu/hr, MBTUPerHR
VarVar (varistor)Var
MillivarmVarmVar, Millivar
KilovarkVarkVar, Kilovar
MegavarMVarMVar, Megavar
TorqueFtLBFFoot pounds forceft-lbF, FtLBF
NmNewton meterN-m, Nm
LengthftFeetft
InInchesin, In
mMetersm
mmmillimetersmm
cmcentimeterscm,
milsa mil = a thousandth of an inchmils , MILS
μmMicrometersum
MassPoundslbmlbm, Pounds
Kilopoundsklbmklbm, Kilopounds
Kilogramskgkg, Kilograms
ElectricCurrentAmpsAA, Amps
MilliampsmAmA, Milliamps
KiloampskAkA, Kiloamps
ElectricPotentialVoltsVV, Volts
MillivoltsmVmv, Millivolts
KilovoltskVkV, Kilovolts
TimeSecondssecondsseconds
Minutesminutesminutes
Hourshourshours
Daysdaysdays
Yearsyearsyears
StmSpecificEnthalpyBTUPerLbmStem Table Function, Specific Enthalpy British Unit, Btu/Lbmbtu/lbm, BTUPerLbm
JPerkgStem Table Function, Specific Enthalpy SI Unit, J/kgnot found ?????
kJPerkgStem Table Function, Specific Enthalpy SI Reference unit, kJ/kgkJ/kg, kJPerkg
BTUPerLbmFStem Table Function, Specific Entropy British unit, BTU/Lbm/Fbtu/lbmf, BTUPerLbmF
kJPerkgKStem Table Function, Specific Entropy SI unit, kJ/kg/KkJPerkgK,
JPerkgKStem Table Function, Specific Entropy SI Reference unit, J/kg/Kj/kgk, JPerkgK
StmSpecificVolumeCubicFeetPerLbStem Table Function, Specific Volume British unit, Ft^3/Lbcubicfeet/lb, CubicFeetPerLb
CubicMeterPerKgStem Table Function, Specific Volume SI unit, m^3/kgcubicmeter/kg, CubicMeterPerKg
StmThermoConductivityBTUPerHrFtFStem Table Function, ThermoConductivity British unit, BTU/hr/ft/Fbtu/hrftf, BTUPerHrFtF
WattPerMeterKStem Table Function, ThermoConductivity SI unit, Watt/m/Cwatt/meterk, WattPerMeterK
StmDynamicViscosityLbmPerFtHrStem Table Function, DynamicViscosity British unit, Lbm/ft/hrlbm/fthr, LbmPerFtHr
CentipoiseStem Table Function, DynamicViscosity SI unit, Centipoise, 1e-3 kg/m/scentipoise, Centipoise
PaSecStem Table Function, DynamicViscosity SI Formal unit, Poise (analog to Pa * s), kg/m/spasec, PaSec